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Applied ClinicalTrials

How can eClinical deliver on the vision?

Although EDC has taken a tighter grip over the last 5 years, replacing Paper as the primary medium for capturing clinical trial data, often, the value of EDC is not being realized.

I have certain theories as to the root cause - some of which I have witnessed first hand. The question is, what can be done to tackle these barriers to progress?

PROCESSES

Such a simple issue on the surface, but so often being the primary reason for failure to achieve ROI. Here are my 6 reasons why poor Processes impact efficient clinical trials

1. Processes are not re-written to take advantage of the end-to-end impact of EDC.
   
2. Processes are left as generic, therefore failing to leverage the capabilities of specific EDC systems over others.
3. Process Silos - rather than having a set of processes that work efficiently across Clinical Research, processes are developed within the different departments - Protocol Authoring, Study Build, Data Management and Programming / BioStats. This means that potentially work carried out in Study Build is detrimental to what occurs in Data Management and in BioStats.
4. Process Bloat - Processes are developed to such as level of detail, that they become a hindrance to getting the job done. Processes should not instruct the reader on the use of a System User Interface. Processes should guide, but not replace the skills and common sense of trained staff.
5. Process Training - Writing the processes is the easy part - communicating these processes in a way that staff understand and follow is where it becomes tough. eLearning, wiki's and other such tools can change the endless tedious reading into 'knowledge on demand'.
   
6. Processes are good for business first and foremost, and secondly to support a company comply with rules and regulations. Often processes are seen as a necessary evil in a regulated environment.
   

CONSERVATISM

Often when implementing EDC organizations work on the basis of :- better do what we did before, in addition to what we do with EDC.

So - it may be the case that EDC is programmed by Data Management to check virtually all the data, but, just in case multiple subsequent reviews are carried out before the datapoints and therefore database is locked. Studies have shown that a negligible amount of data is modified after it has been first entered. It is really efficient to check, re-check and further check data, if the results have such a minimal effect on the quality of the resulting data?

CRA Monitoring duties related to the clinical data reduces by around 75% in comparison to paper studies. No more logging of enrollment, patient visits, SDV or such things. This should all be automatically captured by the EDC system and communicated through reporting, or a status portal. Repeating this is simply a waste of effort.

STANDARDS

The use of standards is a popular topic. CDISC have made great leaps. However, the actual resulting savings in the application of standards have often yet to be seen. Poor tools should take some blame, but also poor work practices. If 50% of a study is equivalent to a previous study, then the Design, Development, Testing and Programming should reflect equivalent savings to the degree of re-use. In reality, 50% re-use often only creates a small % saving.

PROFIT/POSITION PROTECTION
This applies to sponsor companies where big departments have built up as well as to CRO companies that maintain the perception of the need for old (timely) work methods. Put simply, if it takes longer, or cost more to implement and execute a clinical trial using EDC, then something is wrong. I appreciate that exceptions exist - i.e. on very small studies. However, even in these circumstances, standards can creating savings, and improve quality.

Within Sponsor companies, departments can be keen to protect their existence, even if this is at the cost of the company and efficient R&D as a whole.


SOLUTIONS?
Increasingly, I feel that we will see value and risk based assessments. For example, if traditionally, the BioStats / Programming group have re-checked the data that is delivered from Data Management, then unless they are able to prove that the efforts they applied have had a sufficiently significant impact on the final data, then, they will not be performing that task in the future. Similar situations will occur across other areas.


I would be interested in hearing of other experiences in how eClinical systems fail to achieve either quality or cost savings.

Linking SDTM / ODM for better FDA Submissions

If this is not already underway, I think it is time that we examined how we can do a better job of combining SDTM data submissions with ODM data and metadata.   The following commentary is hopefully going to raise some comments, and, ideas as to next steps.

The Challenge

CDISC SDTM – the standard for the Submission of Clinical Data for New Drug Applications - is challenging to work with for a number of reasons.  Data is structured per Domain, rather than per CRF – quite rightly in my view – however, this re-modeling does create a number of issues that deserve to be addressed.

First of all – getting the data into this format in the first place.  In a typical EDC system, you have data captured across many pages.  Often these pages contain 1 or more domains for data.  Data is presented in nice friendly CRF Page like formats, with quick links to audit trails, queries, comments etc.   In the SDTM world, things are not quiet as friendly.  You have long lists of records structured by domain.    You cannot see the audit trail.   You struggle to relate the comments.  The queries may not even exist.

Now – ok – maybe the audit trail and query log should be of no significant relevance to the Medical Reviewers…  It is supposedly more evidence of the data cleaning process having taken place. Maybe that is just a carry over from working with paper CRF’s for decades. However,I would argue that data is never 100% clean.  It is sufficiently clean to merit safe statistical analysis.  Reviewers may feel that in a position of doubt, that they would like to see context behind the data being recorded, and therefore see the query and audit logs.

So – after that short ramble – how could we make the life for Reviewers better?

Combining ODM with SDTM

Well, first of all, why not leverage the standards we already have for clinical data – ODM and SDTM – but combine them in a more effective way to offer  SDTM directly linked to ODM?

What I mean by this – and I am sure XML4Pharma will point out that this has been suggested previously – is that we extend the ODM specification to accommodate SDTM Domains within the ODM spec, AND that we provide the means to link the SDTM domain content with the associated eCRF data & metadata in the present ODM.

To the end user – this would result in a mechanism to switch between a tabular SDTM view of data to an eCRF view of data, with ready access to the audit trail and queries, as well as potentially a better context of the data in the way it was captured.

Easy to achieve?

Sponsors struggle to create SDTM today.  However, I am not certain that this is due to underlying faults in SDTM itself.  I think the tools will mature, the standards will mature, and sponsor companies will simply get better at it.

Creating related ODM is also not too difficult. Any EDC vendor for instance that wish to be credible in the marketplace need to be able to offer data and metadata in the CDISC ODM format.

Programmatically linking the SDTM and ODM is probably the hardest part.

In theory, you could have a situation where every field that exists on a SDTM records belongs to a separate ODM page instance.   The problem can be solved, but, it is not going to be easy.

Conclusion

Delivering SDTM data in a ODM style format, and creating a means to link the SDTM/ODM to the present ODM data and metadata will create data that is considerably more useful for both analysis, submission and archiving.

Apple iPad and eSource

The Apple iPhone broke new ground in offering an all in one device for Music, Phone, Games, Organizer and general applications.  Other companies had introduced almost all the concepts. It was Apple that brought them all together so effectively.

I have considered the suitability of the iPhone specifically as a device for capturing clinical trial data.  The obvious application is an eDiary device. People familiar with the iPhone will be aware of the phenomenal success of the App Store.  It may be possible to write an eDiary app.  However, there are challenges with metadata deployment and application patching that might prove insurmountable given the restrictions that Apple place in deployment.  As far as using the native browser on the iPhone – the form factor is just not that suitable. Yes – you can fill in a browser based form, you can do the 2 fingered pan and zoom. But, it just doesn’t quite fly when it comes to regular data entry operations.

Shortly, Apple will release the iPad.  In many ways this is like an iPhone or iTouch, but larger. Form factor wise, it is similar to many Tablet PC’s. However, it has the advantage of being tied to the iPhone/iTouch OS. It will also be provided with both Wifi and 3G connectivity.

One of the real boundaries to eSource in clinical trials is the portability and availability of the device at the appropriate times.  With the larger touch screen of the iPad and the option of connectivity with either 3G or Wifi, it will be increasingly possible to efficiently capture data at the place of data availability.

So – could the iPad break the capture to paper / transpose to EDC bottleneck at the sites?  I think so.  The solution is likely to be browser based though – App deployment is still too restrictive.  It needs to be fully touch screen friendly.   It needs to make it beautifully easy for an investigator to ‘interview’ a patient, and key the data during the interview where appropriate.   It needs to provide a means for the investigator to indicate through a simple highlighter pen style UI metaphor that data is being entered as source, or, being transposed from source.

I appreciate that other devices exist today that perform a similar function, but, I believe the connectivity, general ease of use, and low price point will make the iPad stand out.

One critical feature may be the Electronic Health Records link.  I think the data that should be copied needs to be at the discretion of the site personnel. I am not yet convinced that data privacy together with a sponsor controlling the study build /  data propagation is viable right now. A really simply copy/paste mechanism might be better than nothing in the time being.  We will need to see how well the Safari browser performs.   

Initially, I see the iPad making inroads within Phase I units.  Hardware device interfacing is less of an issue here now – most devices should be looking at centralizing the data interchange, rather than sending it directly to the data entry device.  Web 2.0 interactive technologies will allow developers to create some of the realtime functionality that dedicated Phase I solutions have enjoyed in the past.

I am looking forward to seeing the first iPad EDC demonstrations at the DIA in June!

Value of Batch validation?

One of the questions often asked of EDC systems is ‘Where is the batch validation’.  The question I would like to ask, is what is the value of Batch Validation versus Online Validation.

I should start by saying that I have a personal dislike of technology that works in a particular way – because that is the way it has always worked – rather than because a pressing requirement exists to make it work the way it does today.

Performance – Batch Validation generally dates back to the good old days of batch data processing.  With Clinical Data Management systems where the act of entering data, and the triggering of queries were not time critical, batch processing made sense.   The centralized Clinical Data Coordinators would double-enter the data rapidly, and at an appropriate point in time, the batch processing would be triggered, and the appropriate DCF’s lined up for review and distribution.

For EDC – things are different.   It is all about Cleaner Data Faster. So not data checking immediately after entry creates an inherent delay.   No site personnel want to be hit with a Query/DCF hours or even days after data was keyed if it could have been highlighted to them when they originally entered the data – and, presumably had the source data at hand.

A couple of CDM based tools provide both online edit checking, as well as offline batch validation.   The Batch validation elements come from the legacy days of paper CDM as per above.  The online checking is a subsequent add-on created due to the difficulty of efficiently parameterize and executing Batch validation checks per Subject eCRF.

Lets have a look at a couple of other differentiators.

1). Online edit checking tends to run within the same transaction scope as the page – so, when a user sees the submited page – they are able to immediately see the results of the edit check execution.   This means the data submission and edit check execution for all checks must occur in less than a couple of seconds in order to be sufficiently responsive.  With Batch Validation, running across data can be more efficient, and user experience is not impacted – waiting for a page refresh.

I believe most leading EDC products have the performance aspects of real time edit check execution cracked. Networks are faster, computers are maybe 10 time faster than 4 years ago. I don’t believe that performance is an issue in a modern EDC system with properly designed edit checks.

2). Scope – Batch validation is able to read all data  within a subject regardless of visit. In addition, some are also capable of checking across patients.   EDC systems with online validation also generally manage to read all data for a subject, but do not permit reading across subjects. 

3). Capabilities – Most EDC systems edit checking mechanisms are application intelligent, rather than based on SQL or syntax that interprets down to SQL as with Batch Validation.   As a result, the syntaxes tend to more business aware. If you are having to write code – SQL or other syntax, then you have a demand to validate the code in a similar fashion to the vendors validation of the system itself.  Avoiding  coding in favor of a configuration / point and click tool makes the testing considerably easier with automation possible.

4). Architectural Simplicity – If you were a software designer, and you saw a requirement to check data that is entered into a database.  Would you create one syntax, or multiple syntaxes?  Even if  you saw a need for offline batch validation – I think you would go with a single syntax.  If you have a means to balance where and when the rules run, then that might be ideal – either at the client side, application side, or database layer.  Using 2 or even more syntaxes would be something you would avoid.

5). Integration implications – Data that is imported into an EDC or CDM system should go through exactly the same rules regardless of the medium used to capture it - Browser, PDA, Lab, ECG etc. This even applies if you are importing ODM data.  If this is not the case, then downstream data analysis needs to confirm that the validity of the data against the protocol was assured across the devices.  Managing to achieve this if you have separate batch and online edit checking is difficult.

 

On re-reading the details above, it sounds a bit like I am bashing systems that do Batch Validation.  That is probably slightly unfair.  I have worked with both EDC and CDM systems, and written checks for both. In the paper CDM world, the User Interface for the batch execution of rules makes sense. You choose the appropriate point in time, and, you can determine the scheduling and scope of DCF’s.  So – for a pure Paper environment, this meets requirements.

However,  in an increasing EDC world – I am not sure this has value.  It could be argued that it gives you the best of both worlds.  However, I think it is an unsatisfactory compromise that increases complexity when migrating to focus on EDC. It simply does not create a good scalable solution.  Users will be left wondering why things are so complex.

CDASH, SDTM and the FDA

Hurrah!  The FDA have made an announcement on their preference towards SDTM!!  Well.   Sort of.   They met up with representatives from CDISC. The CDISC organization wrote down some notes on the discussion, and posted them to their Blog.

Ok – maybe I am being overly flippant. However, why does this message need to come out by proxy from CDISC?  Why can the FDA CDER / CBER not step off the fence and make a firm statement on what they want, and when they want it?

One point made was that applying CDASH is the key to attaining SDTM datasets.  Well.  Sort of.  It is a good start point. But, it is only a start point.

The CDASH forms are very closely modeled on the structure of SDTM domains.   Do I always want to capture one domain, on one eCRF form – not always.  Do I want to sometimes capture information that is logically grouped together according to source documents that belongs to multiple domains on the same eCRF – often I do.  We should not compromise the user friendliness and therefore compliance at the sites because of a need to capture data according to the structure of the data extracts.

CDASH was developed around the principle that the EDC or CDM system modeled eCRF’s to equal SDTM domains.   If your EDC or CDM system does not do that, then compliance with CDASH is not entirely valuable.

However – or rather HOWEVER – if you fail to apply equivalent naming conventions to CDASH/SDTM and fail to use matching Controlled Terminology, and, you expect to achieve SDTM – you will be severely disappointed. Achieving SDTM will not be hard – it will be virtually impossible.

With regards to the statement that applying CDASH can create 70-90% savings.  That is not the whole story.  Apply CDASH + standardizing all of the other elements such as rules, visits etc – and automating testing and documentation – yes, then you can achieve a 70-90% savings.

CDISC Rules 2

In my last posting, I discussed potentially using ARDEN as a syntax for expanding CDISC ODM with rules.

After a couple of months of on and off investigation, I have decided that ARDEN is dead as an option. Actually, ARDEN is largely dead as a potential syntax in general.

The value of a rules syntax lies primarily in the potential ability to put context around data once it reaches a repository or data warehouse.

In theory, the transfer of rules would be of value in transferring a study definition between systems. However, I cannot think of a really valuable situation where this might happen. If data is captured into an IVR System and then transferred across to EDC - does it really matter if they both have access to the rules? Instead, the rules could be applied by one of the systems.

That last point takes me to the other reason why rules are less critical. If the last decade was about standards development this new decade must be about standards application - and, in particular the real time exchange of data between systems. The need to validate data in System A first, before transferring it to System B is only really necessary if System A cannot check directly with System B. With the increasingly prevalent Web Services combined with standards - it will be possible to carry out these checks online.

CDISC Rules!

Ok, so a play on words. CDISC may rule in the field of Clinical Data standards, but, it does not rule in the standardisation of rules associated with data.

Let me expand here for those not familiar with the issue.

CDISC ODM provides a syntax for the definition of metadata (and data) used in the interchange of information between (and sometimes within) systems. CDISC ODM does not scope the definition of edit check rules that are applied to the data when it is captured. I feel that is a significant omission as the rules element of the data a) take a considerable time to develop and b). provide a context to the data.

Question - So, why do we not already have rules built into the standards?

Answer - rules are often technology or vendor specific. There are almost as many methods of implementing rules, as there are EDC products.

Question - Why not define a standard mechanism for creating rules that vendors could either comply with, or, support as part of interfacing?

Answer - Well, it all depends on what you want the rules to do. In their simplest form, rules are boolean expressions that result in the production of a Query or Discrepancy. However, many systems go well beyond simply raising queries. The boolean element of the rule may be consistent, but the activity performed in the situation that the boolean returns true, is often very vendor specific.

Lowest Common Denominator

So - lets assume that we are looking at implementing a lowest common denominator of rules and actions that the majority of systems support, and require

What can we do to standardize a syntax. Three options I think;

1) Choose a syntax from one of the leading vendors,

2). Develop a new syntax building on existing ODM conventions

3). Bring in another standard syntax, potentially already in the Health or LifeScience field

Lets look at them in order.   

No. 1 - Choosing a Leading Vendor Syntax is probably great for the chosen leading vendor, but, bad for most other vendors. A benefit though would be that it would already be proven as a means to represent rules and actions in a clinical study. Some syntaxes are based around standard tools such as Visual Basic for Applications, JavaScript or even SQL. This approach may create almost insurmountable boundaries for other vendor systems that do not, or cannot implement the technology - for example, it is not easy to interpret VBA on a non Microsoft platform. So - option 1 has some potential, but, depending on the chosen vendor, may result in closing the door to the standard for others.

No. 2 - Creating a new Syntax would result in something most vendors would be happy with, but, would require considerable effort from the contributors in order to develop a complete specification for the standard, as well as a reference implementation. The advantage of such approach would of course be that it would be seen as a common standard open to all, and not specifically biased to any one vendor company. In practice, the technology approach chosen would favor some more than others.

No. 3 - Leverage an existing Syntax may well bring the benefits of No. 2 without all the costs of designing something from scratch.

Ok, so lets say we go ahead with option 3 - what are the candidate standards for rules in the Health and/or LifeSciences are?

As far as I can tell, not many. In fact, I was only able to find one candidate that had any level of success - a syntax called ARDEN.

ARDEN has existed since 1989 as a syntax for describing Medical Logic. Similar to typical Rules in EDC, they are defined in Modules - Medical Logic Modules - and called based on the triggering of an event.

[For an accurate definition of ARDEN and its roots, check Google Books - search for ARDEN Syntax and examine Clinical knowledge management: opportunities and challenges By Rajeev K. Bali, Pages 209 --> 211]

As a syntax, it is mostly general purpose. Here is a snip from an Arden Syntax module,

logic:

if

last_creat is null and last_BUN is null

then

alert_text := "No recent serum creatinine available. Consider patient's kidney function before ordering contrast studies.";

conclude true;

elseif

last_creat > 1.5 or last_BUN > 30

then

alert_text := "Consider impaired kidney function when ordering contrast studies for this patient.";

conclude true;

else

conclude false;

endif;

;;

In the example, you can see that the syntax uses standard if/then/elseif/endif constructs. Assignments use the := combination etc.

HL7 have a section dedicated to ARDEN here. The activity appears to be limited with no Postings or Documentation since 2004. On walking through some of the presentations, some of the consumer companies such as Eclipsys were proposing extensions to the syntax - for example to add object definition support. It would appear that the take-up of the standard has been limited to those organizations that had a problem to solve in the EHR area, and wanted to re-use a syntax, instead of inventing their own.

The fact that HL7 has lended support for ARDEN may be sufficient in itself. However, we would need to dig considerably deeper to understand how ARDEN syntax would fit with a syntax such as ODM. The first challenge is the conversion to an XML form. There are plenty of articles on ARDEN XML for further reading.

RuleML is another standard that may address the need to create Rules, as well as meeting the perceived need of being XML based.

More about ARDEN and RuleML in a later posting I think. This one is quite long enough for today.

Source to eSource with EDC

One of the areas that I have felt for some time as being a compromise to the effectiveness of EDC, is the subject of Source data, or rather, the fact that source data is often not entered directly into an EDC system.

I appreciate that we have situations where this is impractical for logistical reasons - location of computers, circumstances of source data capture etc.

However, often, it is mandated by the sponsor that source data is not logged in the EDC system, but is instead recorded elsewhere first.   Some advocates will indicate the need to comply with the regulations that state data must remain ‘at the site’.   Personally, I don’t concur with this assessment. The data is ‘at the site’. The cable connecting the screen to the computer might be very very long (the internet) but the data is constantly available at site. I probably shouldn’t be flippant on this point, but, the conservatism in conflict with progress strikes a nerve.

Transposing information from paper to an EDC screen introduces the potential for error.   In the old world days of paper CDM, we had Double Data Entry as a method to confirm transcription errors did not occur - 2 staff enter the same data from the paper CRF’, and the differences flagged/corrected.   With onsite EDC we don’t have Double Data Entry, but, we do have Source Data Verification. Instead of 2 staff sitting next to each other double keying data, we have a monitor fly in to perform the 2^nd check. Yes, I know, they carry out other duties, but still. This seems like an enormous effort to check for transcription issues. It also has a massive effect on slowing down time to database lock.

So – where are the solutions:-

1). Data at Site

We could put on our ‘common sense hats’ and make a statement that allows the entry of source data into the online EDC system. I know of a number of EDC companies that have simply placed this in their procedures. No audit findings / concerns have been raised as a result that I am aware of. Come on Regulators – why the delay in making a statement on this subject? The confusion caused is creating a measurable delay in bringing drugs to market!

2). Physical availability

This one is harder to tackle. When you have data to log, do you always have access to a system/device to log the data? Possibly not. Do you simply try to remember it, like an Italian waiter remembering a dinner order… I don’t think so. We either need to provide portable data entry devices, or, we accept paper transcription for these elements.

3). Differentiating Source from eSource

This does open up one area of concern. If we have some data as source, and some as eSource, how do we know which is which? When a Monitor goes looking for the source data, if they don’t find it, does that make it eSource – no.   There needs to be some very simple flagging, and visual indication system built into such a mixed source/esource system that supports this. I have seen this in one system, but, it is very rare. Come on EDC vendors – you’re turn here!

4). Other systems

Health Record systems amongst others will often be the first point of entry for data that may apply to an eCRF.   The current approach for organizations such as CDISC and HL7 is to create interfaces between systems. This will be a slow burner, I predict. There are so many hurdles in the way. It requires active cooperation from both sides – EDC providers may be fully onboard, but, I am not so sure about most EHR providers.  

We may see a company emerge (maybe this is what some former PhaseForward employees are up to – who knows!) develop an online Clinical Development Electronic Health Record System that is immediately EDC ready. Of course, with such a small deployment potential, I am not sure that we will see this appear at all sites in a global study, but for domestic application – say within a single country, inside research hospitals, it could work. I digress - back to the integration issue – yes, when we have standards, the feeds will start to happen, but not for many years.

5). Patient Recorded Information

ePro, Patient Diaries etc.   These are increasingly realistic, for the right sort of study for the accurate capture of patient data. If used appropriately, they can cut down the volume of data that needs to be transposed into EDC, and therefore source data verified.

On a side note, I am sure we will see a downloadable iPhone app that will make the current hardware/software dependent or basic PDA browser based systems seem old and tired.

The advantage of diary based systems is that instead of an investigator quizzing a patient, writing down the responses, transposing the responses etc. The information is captured ‘at source’ often considerably closer to the time of event.

Expanding from my previous post, I expect to see systems like PatientsLikeMe expand onto portable devices and act as an entry point for both patient identification and data entry. Internet enabled device pervasiveness will simply make this happen.

Conclusion

A lack of eSource has direct impact on the time it takes to lock data. With adaptive clinical trials executed by forward thinking sponsor companies, the point at which an adaption can occur corresponds directly with how long it takes for the sample size end-point significant datapoints to achieve a locked status. To simplify - the less eSource you have, the longer your studies will take. Forget a few days - we are talking wasted months.

Applying Social Networking system principles to eClinical

Social Networking software is one of these technologies that has just sneaked up over the last 5 or so years.  We have sites like Twitter, Facebook, Bebo, MySpace and LinkedIn all vying for marketshare attention.  Like all new business areas, segmentation is occurring with Bebo aimed towards kids, MySpace adults and celebrities etc.  Over time, I am sure we will see accepted leaders in the same way Google leads the search engine pack.

For a number of years, we have seen small clusters of information sharing sites aimed at specific disease types.  PatientsLikeMe was one of the early success stories with an initial focus on ALS (Lou Gehrig's disease).  It is beautifully written with a user interface specifically designed to be accessible and approachable. [It is also open source, and written on the modern new platform - Ruby on Rails].  Sharing experiences, discussing issues with other sufferers, and learning of potential therapies when dealing with chronic debilitating diseases is an ideal target for the social networking concept.  For something like ALS, where patients are geographical dispersed, a site like this can act as a electronic 'drop in centre' providing a level of support not possible with any other mediums.

An example on PatientsLikeMe is one of the focus communities that supports Devic’s neuromyelitis optica.  This is an incredibly rare disease, often confused with MS that only effects a few thousand people in the world today. As of July 2009, the site has a community of 140 suffers, more than 5 times the population of the largest published clinical study.  The home page for this site is a lesson on how to provide a site that the target users will return to;

Without having to login, or register, the site show a list of treatments and symptoms that have been shared by the 140 patients that have previously registered.  What better way to encourage mutual sharing and involvement!

A replacement for Traditional Clinical Trials?

To a degree PatientsLikeMe and other health focused social network sites are providing an open source equivalent to clinical trials.   Clinical trials are highly structure organized affairs, tightly bound by regulations and rules.  In this way, they are similar to a formal software development approach where specifications are prepared, code developed and testing carried out.  Compare this to open source community approach in software development. Thousands of individuals all  contribute, self regulating, to create products that many would argue are as good, or even better than their commercial cousins. With social networking health sites you have a very large community all contributing on an ongoing basis both in terms of the raw data, but also, the analysis of the raw data to determine trends.

With a typical clinical trial, a subject with be interviewed by an investigator, measurements taken, and information recorded into a system according to pre-prepared protocol.  Together with the terms of the protocol, the investigator will be in a position to make an assessment as to whether the subject is sufficient compliant for the corresponding data to be considered part in the overall data set going forward.  With a patient community approach, the compliance with an fixed regime, or protocol will be limited.   The sample size must therefore be considerably larger in order to make any kind of assessment based on the results.  Also, there are considerable challenges in determining the degree of compliance. Statisticians would most likely struggle to offer up a statistically safe trend based on the variability of the surrounding conditions, many of which would potentially be un-recorded.

How about as an entry point?

Nothing new here of course - PatientsLikeMe are already partnering with commercial companies, but, potentially a more open approach would be to create bridge between the community and the commercial world by leverage standards to create an opt in gateway.  Sponsor companies could publish a set of entry criteria and schedules for clinical trials through a protocol standard language (CDISC PRD ?) push approach. Community health portals could utilize these criteria to determine a filtered list of individuals that comply and then give them the opportunity to opt into the published study.

Maybe it would be a shame if the 'big bad' commercial world started to spoil these not-for-profit community led efforts.  I am not sure.  I think both could benefit.  Patients that suffer these diseases are actively looking for therapies and help.  If the drug companies are better able to target and develop these study therapies, then surely it is a win/win.

eClinical Vendors - Build or Merge

Over the last year, we have seen a spat of eClinical companies either swallowing up smaller players, or, merging.   The recent procurement of eTrials brought this to mind. From a capability checklist perspective, this looks good.   As a sponsor, instead of going to many companies for many systems, they can be procured from a single source. If problems occur with a system, there is only one number to call.  If the systems aren't speaking, then no finger pointing - the single vendor is responsible.

However, with today's eClinical systems demands, I believe some challenges exist particularly related to scalability and metadata management.

In former days, where Client/Server solutions were the norm, and, the cost of setup and integration was just an understood overhead of working with eClinical systems, mergers made a lot of sense.  It often took months to fully configure a platform, carry out validation and adjust the configurable settings to make it work as required.  If the system came from 2 sources versus 1, it didn't really mater as much, as it was expected that it would take considerably time and cost to make everything work anyway.

The technology landscape today is very different.  In a Software or Platform as a Service model, sponsor companies are looking for a number of capabilities that can potentially conflict with the abilities of separate products coming from different sources.

How long should it take to setup an eClinical product so that it is ready to be configured to support a clinical study?  3 months, 1 month, 1 week, 1 day?     In a capacity managed, multi-tenanted Platform as a Service environment anything more than a day is too long. Organizations are increasingly expecting instant capacity support, and immediate responsiveness.

Let us imagine a hypothetical case study. 

A company has developed a nice multi-tiered Java EE web app, with horizontal scalability - things are looking good...  the operational configuration and management of the platform has reached a point where an instant 'on' is a reality for clients. There is a single location for user and metadata management. Security is looking solid, a development plan is in place to expand and extend the core software... and then bang...

... a merger occurs...  The companies IT Hosting group are handed an entirely new platform to co-exist with the current platform... the R&D group inherit a new technology.  This one is .Net, on a different database, using a different app and web server.   Both applications are large and complex - a complete re-design is out of the question.  So, what next?

Well,the first thing that might happen is that the systems are made to appear integrated.  A common User Interface, often called a 'portal' is created that gives the impression that the independent systems are operating closely together.

Next, an interface.   Integration would be nice, but, as the two products were designed in isolation, they don't share a common architecture or platform stack, so, an interface is the only viable solution.  Both products are not standards interface based so hard-coded bi-directional feeds as put in place.

Ok, so they share an access point, and, they share data, but, do they provide an effective solution?

CDISC & Standards

CDISC may offer potential to organizations that choose to buy rather than build.   One of the key objectives of the CDISC standards are to achieve cross system interoperability.   If the disparate systems are capable of offering CDISC ODM integration - both data and metadata - then the challenge may be less steep. 

We are also seeing the emergence of Web Services, often leveraging CDISC standards, that in theory will allow the non programmed bi-directional interchange of data and metadata between supporting systems.

The question though ultimately is, will the resulting systems deliver solutions in the way the customer wants a solution, or, will the the customers end up with having to work in a convoluted way, because that is they way the systems came together, and that is the way they need to work.

I will not expand on this commentary for now as I am interested in hearing experiences from those that have faced, or are facing these integration challenges.

Too busy for EDC?

 

When things are busy, people tend to become more re-active than pro-active.  Instead of working on a list of tasks that are set out according to a pre-prepared plan, tasks are tackled as they come through the door.   Email for example is often a curse in this regard.   The priority of work tackled is often related to the order that an email appears in your inbox, rather than any real priority for the underlying work.

With a blog, it is necessary to proactively go and monitor feedback.  If you don't go to the blog site, you don't recognize the feedback.

EDC can be impacted negatively by this.   Imagine you have very busy site personnel - not hard... Typical online EDC systems contain workflow that often demand pro-active interaction.   A Monitor might for example create a query on data that requires a response from site personnel.   The turnaround time for the query is dependent on the frequency that the site personnel access the EDC system.   For smaller sites without dedicated study personnel the likelihood of an investigator simply not finding the time to login to an online system to look for pending actions.

ECO made a suggestion a few months back regarding the potential use of RSS Feeds - a simple concept with a technical name - whereby such feeds could be used to notify a participant of a particular action.  For example, if a Monitor raised a Query, then this would trigger - at the discretion of the recipient, an RSS / email notification that the action is exists.  The recipient would then click on the link, login, and carry out the action.

So, questions -

Would this cause security concerns?  If the feed included information that might be considered patient confidential - then yes. However, the actual requirement to include any real details in the communication is limited.   The message could simply say 'You have a new Query on Subject xyz'.

How would this be implemented?   Certainly a system or study switch from the sponsor to make it available.  Next, it should be optional at the user level - when a user signs up, they could opt in for correspondence when things required action, by type.  After that - it would be relatively automatic to the users.   As far as the technology - relatively easy for web based systems provided outbound communications don't cause security issues.

Would this be called an 'RSS Feed' - Why should it?  It tends to be teenagers that recognize the term.  On the other hand, ask an investigator if they would like to be notified of actions they need to be performing - that is understandable.

So, a question for blog readers.   Anyone aware of an EDC system that is already doing this?   Maybe this is already an existing feature in Medidata Rave or PhaseForward Inform products?    Like to share some experiences?

EDC Study Startup Time

EDC Guru left a comment on the Top 10 mistakes made when implementing EDC posting.  In this comment, it is suggested that one of the potential failure areas is not leaving sufficient startup time when switching from Paper to EDC.  I fully agree, although, from a sales perspective, the alternative is the sponsor goes to another CRO or Vendor that will offer the required timeline.

If you speak to an EDC company, one of the metrics they often pride themselves in is the time to First Patient In.  12 weeks, 10 weeks, 8 weeks or even 6 weeks are banded about.  This is clearly a metric worth considering, but, what actually is included in these weeks?   Is that how long it takes the vendor or CRO to *do* the study build, or is that how long it takes for a sponsor to be ready for EDC.

I would put forward that any sponsor company that goes from no experience to executing EDC studies in 12 weeks will not demonstrate the full benefits with EDC. In fact, there is a danger that the experience will be sufficiently poor as to impact the ongoing acceptance of EDC in an organization.Unwisely implementing EDC can result in similar metrics to paper studies, but at considerably extra cost.

So - what is the solution?  Do I think that drug programs be delayed for the benefit of EDC technologies?     Well - no, but, should an EDC based study be delayed until the organization is sufficiently in tune to the experience - yes.

So taking the above as accepted, what are the boundaries to achieving a better prepared company?

1). Senior Management within sponsor organizations will measure the success of a drug development program but the compounds that go in the various phases of study.  Placing a delay in startup will appear like a failure

2). It is very difficult to develop effective EDC processes :-

• Sponsor companies new to EDC do not have the experience to determine where the eClinical tools brings benefits and where other methods are better.
• Vendor companies tackle the process problems from the perspective of technology rather than by tackling the actual business requirements.
• Consulting companies deliver non adventurous palatable process solutions based on regurgitated generic concepts.

3). Silo structured organizations may not offer broad department support for process changes that will make a company wide eClinical approach successful.

 

Ok, so I have managed to point out 3 potential problem areas, so, what is the solution.... or rather, what is my take on a potential solution?

1) Senior Management -

the measurement of success is as important as the success itself.   I have seen this attempted, but I have not seen a lot of success.  If everything changes, how do you compare 'apples with apples'.  If nothing changes, then what is the point. You need to look for the lowest common denominator. Faster development, lower costs is a start...

2) Processes -

How many readers go along to DIA or similar conferences, and either avoid, or sleep through Process topics.  That is a shame, as it is still the Process, Workflow and Change elements of eClinical that are causing bottlenecks.

You get Technology Guru's that create brilliant eClinical systems. Why not empower a Change Guru that 'gets' the technology and 'understands' the potential for changing an organization.

3). I have just answered 3) with 2).

So - back to EDC Guru's comment.  There is a place for rapid start EDC where the vendor or CRO acts just as they did for an old Paper study, and takes on the bulk of the work to make an effective deployment.  Some benefits will be realized, but certainly not all. I don't think the term 'Start Up' should be defined as study start up.  It should implementation program start-up.  A study will appear, down the road, but, not in the same sentence.

Open Source eClinical - Myths & Facts

I came across a blog / article posted by here that provides a Q&A with Ben Baumann of Akaza Research.  On reading the article, I feel obliged to respond to some of the comments made. 

First of all, I believe that Open Source based systems do provide a valid alternative to closed source products.  I have both developed, and used Open Source systems in the past. Both Open and Closed Source based systems are designed to create a financial return for the companies that develop and support them.  With the Open Source model, the revenue comes from support and consulting with the reduced cost of development shared across a number of organizations.   With Commercial software, revenue comes from licenses, support and consulting.  The cost of the development is higher, but, this cost is typically covered by the corresponding license revenue.

Back to the article. There are a few points that jump out at me as arguments for OpenClinica;

In addition to a full set of EDC and CDM features one might expect in such a system, OpenClinica has  built-in features that give users the ability to set-up their own studies.

Any EDC or CDM system worth their salt will provide functions that give users the ability to setup their own studies.  Good systems will also ensure that an absolute and clear separation is maintained between the configuration of the study and the tool itself. If the tool has to be modified in any way, then you have a validation nightmare each time you run a study.

In short, an organization can make a rapid and highly informed decision whether or not to use OpenClinica without having to go through lengthy vendor-biased demonstrations and negotiations, and rely on a vendor in order to get their studies configured appropriately.

Well... instead of going through a demonstration that presents the features of the product, the user really needs to start digging into the source code to gain a good understanding of what goes on. So, as a user you need to have a good understanding of fairly complex 3rd generation language programming.   To fully understand how a tool works takes some time. For large EDC or CDM systems I would put that estimate, for an experienced programmer, weeks if not months of detailed analysis. 

Enhanced validation. Validation can be much more thorough with open source software. Buying proprietary software is like buying a car with the  hood welded shut-you don’t know what’s really know going on behind the scenes. Open source provides the highest level of transparency making it possible to truly validate a system from end-to-end.

"Oh! so I need to validate the system myself?" Validation is complicated and expensive.  All systems in the eClinical world require that the development runs within a structured process. You generally need to maintain a trace-ability matrix that takes the software through a lifecycle from specification through to coding and on to completed and recorded testing.   As with InHouse systems, maintaining this will can be challenging

Typical eClinical systems split the code product, that is developed and validated, from the configuration of the product. That part is typically just 'tested'.  In the situation, you don't need to re-validate the software product following a configuration of the product for a particular deployment (i.e. Study).  The validation of a full EDC product might take 200 man days. The testing of a configuration might only take 10 days.   If you mix the configuration with changes to the core software product, you need to be very careful that you don't compromise the core product validation.

As I said at the start, open source solutions have a place in the eClinical business area.  They can be the right solution in certain circumstances, but, they are not always suitable.

Modelling ODM Metadata - a response

Today, I would like to respond to a recent comment from XML4Pharma regarding the use, or otherwise of ODM in modelling CDISC based studies. X makes some valid points, but some of the concerns are based more on a misunderstanding of the proposals.

First of all, thank you XML4Pharma for your input – all input is good input as far as I am concerned.

Hopefully, with this posting, I can clarify that I do know the differences between ODM and SDTM!... and yes, I do believe the ODM and SDTM complement each other.

I think you have misunderstood how I am suggesting SDTM be used versus ODM. If you look at my recent post, what I am suggesting is precisely what you have been evangelizing about - to think about the Outputs - SDTM - in order to create the inputs. The principle defined was for the modelling of metadata – how you potentially get to an ODM based definition of a study - not how the metadata is used and processed in an EDC product. 

The difference in my proposal from yours is that I am suggesting a 3 tier model in order to achieve the underlying definition of forms and rules in a study. The end result may well be ODM, but, it is how the ODM is prepared is what I am suggesting. To understand where I believe the challenge is we need to think of the definition of a whole study.

Hypothetically, a typical EDC study build includes lets say 8 days of Forms development and 20 days of rules development. Looking at just the forms, the re-use can be effective from study to study... A second study can be 4 days, 3^rd study 2 days etc. But what about all the associated rules. How will they work when the visit structures change, new forms are included, and fields are taken away. Will we see 20 days going down to 10 days and then down to 5 days... that depends on whether the use and content of forms for a study are impacted... but not if the logic is hanging off the forms.

Lets take an example problem. I have 5 similar forms that all need to populate the same SDTM domain. With the proposed model we start with the definition of the SDTM Domain (Tier 1). This contains the definition of what we are aiming for. It contains all fields, not just the ones we might use on a form. Next, the definition of a superset Logical structure that contains all of the appropriate fields that might used by a sponsor together with logic that is applied regardless of the capture method (tier 2). Finally at Tier 3, we have the 5 different forms. These all subset the Logical structure defined at Tier 2 and inherit the rules. As we have a consistent thread from Tier 3 thru Tier 2 to Tier 1, it is possible to create a definition that can be used by an eventual target EDC product to populate the same Tier 1 (SDTM Domain) regardless of the form structure or logic.

At tier 1, you define as much information as you can that will be consistent across Tier 2 and 3. Fieldname, data type,  etc.  Tier 2 inherits information from Tier 1 and adds relationships and rules.  You might have many logical structures to capture the same information, but, the information in Tier 1 is only defined once.  Tier 3 applies the same idea.  You might have many instances of a form,  that in turn apply the same rules, but one form might be visualized differently from another.

That was a simple example. Lets imagine I wanted to capture data for 3 domains on the same form. We could simply say to the Investigator – sorry, “we need to split this into separate pages, because that was SDTM demands,..” the true answer is that ‘this is what our modelling structure demands’.  I don't think the model should demand it.

I could have an AE form that is captured on a single page in one study, but captured across 3 pages in another study. I could even reach the point were I want to capture AE information on a PDA (though unlikely!). The eventual SDTM Data domain is the same, the rules are the same (I only want to define them once). The only thing that is changing is the presentation.

As you say, ODM does contain cross references back to SDTM - Fields and Domains. This will allow you to map information back to SDTM.  With the 3 tier model suggested, the way in which the Field and Domain (SDSVarName/Domain) are defined is through inheritance. 

I won't respond to the Audit trail and 21CFRPart 11 comments that XML4Pharma made. Hopefully, by this point my explanations have corrected this misunderstanding.

XML4Pharma's last point regarding HL7-v3...

we do already have a format for exchange of clinical data (or is submission not "exchange"?). So formatting SDTM as ODM is a very nice, simple and efficient way.

if I was part of CDISC and wanted to work closely with HL7, or, if I wanted to be considered a bridge builder to Electronic Health Record systems I would probably embrace HL7-v3 without even opening the specification. It may or may not be the best solution... but on paper it is probably the most marketable.  In response, I would recommend that you constructively and diplomatically present the benefits of an ODM/SDTM based standard over HL7-v3 with further real-world examples. Without this sort of approach - as a leading proponent of ODM based systems, XML4Pharma may come across as simply showing bias due to home grown interests. Personally, my gut feel is that you are correct, but, I do not yet know enough about HL7-v3 to make a fully considered opinion. However, I believe there are sufficient intelligent individuals in the CDISC organization to take a considered technical argument onboard provided it is delivered in the right way.

Applying XForms to CDISC

In a previous posting, I made reference to a technology called XForms.  I mentioned that it might prove of some value in addressing the challenges that eClinical systems face in meeting business demands.

XForms is an interesting technology in a number of ways.  To understand what it brings, it should be understood what the traditional method of browser data presentation lacks.  HTML remains the standard means of presenting form information on a screen.  It fundamentally dates back to 1995 in its present state when the Internet really took off. As far as broad standards for forms based data capture, things have not really moved forward greatly since then. 

HTML forms are built in 100's of different ways by software residing on the server.  Typically, the developers will take lots of strings containing things like <Head>, <TR> or <BR> etc and glue them together to make up the necessary codes required to present a form on a browser. Admittedly, there are lots of 'helper' technologies to make things easier such as Extensible Style Sheets (XSLT), Dynamic HTML etc, but, ultimately, there is no one way to effectively create and deploy forms to a browser. In particular, there is no way to easily separate what a Form Does from how a form Looks

The W3c group recognized this challenge and create the XForms standard released October 2003.

'So, yet another standard that will disappear into obscurity!'  I hear you say.  Well, maybe, but, even if it does, it has some attributes that are worth understanding, when considering how things should work in the ideal world.

Benefits of xForms

1. User Interfaces built on XForms require fewer round-trips from client to server - they are more self contained than pure HTML implementations.  This leads to a better, faster user experience
2. Mobile device capabilities vary significantly.  Creating a form interface that works on a iPhone as well as on a 1400x1200 resolution desktop is very difficult. XForms provides the separation to allow this to occur with common code.
3. Javascript is the tool many developers use, on the client browser side, to workaround the limitations of HTML.  However, Javascript is implemented differently by different browsers, and, can even be disabled for security reasons.  XForms provides a means to avoid this limitation.

More about xForms

All sounds cool.... so, lets find out more about xForms...

XForms implements the concept of Model/View/Controller.   Sounds like mumbo jumbo, yes, so lets translate that into some meaningful.

When you capture information from forms, you can define 3 distinct layers to efficiently achieve a design.  

Presentation - 'the View'

Starting at the user side, you have the Presentation side.  On a regular desktop browser, you will maybe have a form presented in a free form layout with 20 questions, nice shaded graphics etc etc.  On a PDA, you want something simply, that scrolls well - so you would have a smaller set of questions, presenting with no fancy graphics, and in a simple list layout.  The Data you are after is the same.  The Logical rules you want to apply to the data are the same - it is only the presentation medium that is changing.

Logic - 'the Controller'

Next, we have the brain.  The part where all the rules exist.   This is not 'eClinical' specific, but, to use an EDC requirement, this is where all the edit check rules exist.  The logic is attached here, and separated from the Presentation Layer in order to ensure that regardless of the layout of the form, or, the device used, the same rules can be applied (and most importantly) re-used.    This controller can be split into two areas - handling requests form the presentation for dynamic activities - as well as processing the results in a common way.

Data - 'the Model'

Finally, the 'what' in the structure. The data resides in the Model - or rather the definition of what data. Aligning with the eClinical analogy, SDTM would be an appropriate specification for the definition of what might exist here.

xForms and CDISC - applying the Model

So, how might XForms be applied to the CDISC in general?   

To some degree, CDASH defines a set of fields that will be captured without consideration of the device that might capture them.  You could have a situation where a PDA might capture 4 questions at a time whereas a desktop browser would capture 20.  The definition of the form itself will differ due to the medium.  So - CDASH in this perspective doesn't fully fit.  However, as a means to standardize the 90% rule - most forms are completed on a full size browser - it is fine. CDASH provides a recommendation of what would be captured together in the presentation layer for one type of device.

So, where would CDASH fit in the XForms Model / View / Controller paradigm?  

Lets look at a possible model for metadata that could be implemented with xForms:-

Starting from the left - the obvious model for the Data (Model) is SDTM.  This would include a list of all of the standards Domains. It could be extended as required, and include sponsor specific extensions structured as per the SDTM standards specification

Next in the middle, we have the Logic (Controller). CDASH could potentially work in this middle tier although you would need to add the logic elements.  A Module could equal a CDASH Domain with all of the potential (required and optional) fields included. 

Finally, at the Presentation (View) the Form. This would be a representation of the CDASH domain with specific controls (drop downs, radio's etc) added and fields not required for a specific instance removed. Multiple instances of the form might exist with the same rules and relationship to the Data Model carried forward.

 

Conclusion

xForms in the context of CDISC and eClinical is not so much a means of capturing the data. Rather, it is a means for modelling the metadata to better support the separation of the data that is needed from the logic that must be applied, and the presentation of how this is achieved.

With a model applied similar to the above SDTM data sets could be quickly achieved while at the same time offering flexibility in the medium used to capture the data together with a consistency in the rules enforced.

I have purposely left out references to ODM in the above article.  It may have a place here, but I will expand on this in a future posting.

Green gone

Following on from the announcement that Datatrak had resolved the contractual disagreement regarding the ownership of the Clickfind technology, Jeff Green has stepped down as Chairman and CEO.

So, who will buy the remaining assets of DataTrak?   At 15cents a share and a market cap of 2.6M USD some company might see value.  I suspect a mid tier CRO might come in see the technology as a sort of 'House Wine' implementation of EDC for sponsors that do not show a preference for one of the big players.

Datatrak back on Track?

After a few months of uncertainty,  DataTrak have announced at the end of December that they have resolved their legal dispute with the former owners of the ClickFind EDC product they procured in 2006.  I am sure that Jeff Green and his team will be somewhat more positive about the prospects for 2009 than 2 months ago.  The share price though remains very low with a potential de-listing due to occur, pending a hearing with Nasdaq.

Hopefully, the company will pull through.  It would be sad to lose one of the early providers of EDC systems.

eClinical in 2009?

So what will the eClinical landscape be like in 2009?   Here is a projection on what I believe will transpire in the eClinical business area over the course of the next year.  As ever, these are purely my opinions, and do not reflect the opinion of the company I work for...

We have seen significant changes over the preceding 2 years.  The number of vendors have shrunk with Medidata and PhaseForward apparently swallowing up the vast majority of new business.   

Oracle have been suggesting the availability of a new, improved product.  If they want to stand a chance against the big 2, then they are going to have to get the EDC portion right this time. Previous attempts were so far from the mark with regards basic EDC functionality and ease of use that they bombed in the market.

Medidata's announcement of Developer Central is potentially more significant.  ClinPage describes this as an API. However, I think that is a simplification that underplays the significance of the release. Back in September, I wrote a blog on Web Services, and how they might impact eClinical.

A number of EDC/CDM vendors have claimed to offer API's - FW-IMPACT and Oracle for example, but many were simply an exposure of a set of Stored Procedures. Techie's developing eClinical systems have talked about a full web service solution for many years. Medidata appear to have take their experiences with CDISC and actually delivered a fully operational solution - a full CDISC compliant Web Service for eClinical data Importing and Exporting.  

Google were the first company to really generate buzz around the principle of an API over the Internet with the release of the Google Toolkit.  With this, any developer with an Internet connection could send a program request - using web service calls - to Google, and receive search responses that they could use for their own purposes.    If the Web Service eClinical API that Medidata has announced is all its potentially cracked up to be, then we should see a long queue of  eClinical providers - eDiary, CTMS etc all lining up to be in a position to offer Medidata Rave real-time connectivity out of the box.

On a technical note, it will be interesting to see if the use of the CDASH standards will be utilized as a means to standardize the metadata used to capture the data.  If this does occur, we could see a simple handshake occurring at the start-point between the two inter-connected systems to confirm 100% compliance with CDASH. If this is the case, then no manual metadata synchronization need occur. In reality, I suspect ALL CDASH based implementations will be customized, but, its a good start.

Back to 2009 forecasting...

The financial crisis will clearly impact the industry.  The smaller companies - BioTech's specifically - will struggle to find cash.  If the development programs they are running rely on a constant cash flow, then they could go under.  This might provide rich pickings for the big companies looking to pick up a bargain, but, potentially at the cost of new innovations.  For the lower end of the eClinical marketplace, things will be tough.    eClinical vendors that can demonstrate lowering costs - especially over paper - will see increasing business.

eDiary vendors will continue to see business grow provided they can show interoperability, and, can manage to keep infrastructure costs down.   We may see an increase in the prevalence of eDiary solutions based around Off the Shelf or pre-existing hardware - the iPhone for example appears to have the ease of use, connectivity  and synchronization capabilities to make it more widely usable then any other OTS product today.

CTMS vendors will increasingly struggle.  The value of such solutions is increasingly marginalized with the enhancements offered by leading EDC system providers.  Similar to the eDiary space, if they can 'play nicely' with the other systems, they stand a chance.  Otherwise, they will be considered unnecessary in the overall eClinical Life Cycle.

Overall, I think we will see the more marginal areas of the eClinical vendor solution business impacted the most.  When finances are tight, the argument for these types of systems will be difficult.  Life Science companies will focus on cost saving and direct efficiency gain solutions.  This will be no time for long term technology prospecting.

 

For those following these blogs, I wish you well for the holiday period, and Best Wishes for 2009.

Return of the 4GL for eClinical - Part 2

In the first part of the series, I described how in the Technology business, Fourth Generation Languages provided a platform for the effective development of database driven application software.   With this instalment, I would like to examine how the principles of a 4GL might be applied in the design of an eClinical Application Development Tool. 

This part of the series of articles will focus on the requirements - in particular for handling rules, and briefly how these requirements might be met with a syntax.  It should be noted that many of the principles apply directly to EDC systems, however, the target application area is not EDC specifically, but rather a full eClinical platform.

Here are the bullet requirement items;

• Triggers - Capable of defining rules that can be applied based on the occurrence of an event
• Powerful - capable of describing all required rules that might arise in capturing and cleaning eClinical Data
• Human readable syntax - it must act as a specification to a user as well as machine readable instructions when executed
• Referencing - must provide a simple unambiguous mechanism to reference data
• Repeatable - must be re-executable
• Multi-Action - Queries - yes, but what about other actions
• Testable - through a black box paradigm, built in self testing
• Speed - must execute very quickly. <10ms per rule on a typical environment.
• Business aware - must provide features that automate certain common business elements typical of eClinical

Triggers

Firing mechanism

Not Winnie the Pooh's buddy, but a logical method of controlling the execution of rules in an EDC system, is to base the triggering mechanism on the change of an input value.  For example, to check if a subject is between the ages of 18 and 65 simply set an input value of the field containing the 'Age'.  When the age changes, the rule executes.

In practice, this works for the majority of requirements, but not for all.  Sometimes, triggers are required based on the change of other study elements or attributes.  For example, it might be required that when a query is raised for a subject, that a rule is triggered.  In this example, this is subject level triggering rather than response value triggering.

To achieve this, the syntax should support the attachment of rules to study objects.  For example a possible syntax for triggering might be;

on change of [subject|visit|repeat|field].[Object Id].[attribute]:

Each object would have a default attribute - this would be applied if not specified.   A sample reference might be;

on change of field.Age:

or

on change of subject.Status:

The default attribute of a field object might be the value. 

Also, the 'on change' syntax would be assumed based on the reference values.  If you referenced the 'age' in a rule, then that would automatically become the trigger point in addition to any 'on change' attributes defined.

Should a rule trigger based on all values being in existence, or, just some of the values?   With EDC application in particular,  a positive response is required - a page that is left blank cannot be assumed to represent no data - it could simply mean the data hasn't yet been entered.  Special consideration is required here.  Readers familiar with eCRF implementations will recognize the common Header question such as 'Have any Adverse Events occurred?' This is often used to interpret missing subsequent values from entries left blank on purpose. From a triggering perspective, rather than looking at value that may not have been entered - such as AE Description - the code would need to first check the AnyAE flag.

Prerequisites

This is a more advanced concept, but important from the perspective of keeping the resulting tool simple.  Looking at the example above.  More thought is required when developed rules when conditional questions are involved.   So - with a dynamic eCRF, how can we simplify things.

A feature I will refer to a 'pre-requisites' that are aware to the rules engine would potentially solve this problem.  It is necessary to relate, at the metadata level the required need for a particular value. In our example, if AnyAE = No, then we would not expect a AEDescription. However, if a rule looked at AEDescription in isolation, it may not work. In reality, the rule would need to check AEDescription AND AnyAE.  Infact, this would be the case on any check that cross referenced the AE eCRF.

Now, lets image we could place a Pre-Requisite rule against the AEDescription field; AnyAE='Yes'.  That rule could meet two purposes.  1). it could control the availability of the field on the page and 2). it could act as a additional criteria for any rule that referenced the field.  With a Pre-requisite principle, the rule would simple check AEDescription.  The AND condition would be automatically added (behind the scenes) based on the attached pre-requisite rule.

The end result to the study developer would be that they wouldn't need to worry about whether or not a value should exist based on other criteria - this would be catered for by the pre-requisites.  The resulting syntax for rules would be easier.

Powerful

This requirement is at odds with some of the other requirements.  How do you create a syntax that can cater for each and every rules situation, while at the same time be human readable, and re-executable.    The answer is that you will never ever create the perfect syntax that does everything.   What you do need, is a syntax that delivers on at least 99% of requirements.  The enhancements to the syntax from that of handling regular expressions need to be business aware.  Constructs for things that are common to eClinical system must be available as standard.  By providing support for these, the need to go outside of the 4GL bounds should be reduced to a negligible degree.

Human Readable Syntax

eClinicalOpinion raised the question of syntax on a comment on Part 1 of the series.  I see syntax applying to all language components.  What I mean by that is that all application components should be representable as a syntax that can be manipulated as free format text through a text editor OR from within an Application Development Environment. The maintenance of the syntax though will depend on the activity being performed.  For example, it might prove easier to create a data collection form (i.e. CRF) through a point and click UI.  The end result though would be a human and machine readable syntax.

So - if the metadata is all described in the form of a syntax, does that mean that the preparation of the syntax cannot be table driven - not at all - a syntax would consist of 3 things - basic language constructs, references to data/metadata and references to application objects. The preparation of the syntax would be through a table driven approach. Lists of metadata (fields, forms etc) would be stored in tables as would list of application objects such as what can be done to a subject or a visit event.

Should the syntax be XML - I don't think so.  XML might be one of the languages for representing the metadata - ala CDISC ODM - but the most effective syntax should be optimized for purpose. XML is not easily Human readable.

A number of other factors govern syntax.  Writing a compiler or an interpreter is not that easy to do well. Also, the execution of the resulting interpreted or compiled code needs to be fast. If the code that is produced needs to be processed many times before it reaches the executable machine code, then the length of time it takes to execute is longer. 4GL's are processed through 4 iterations. There are answers. For ECMAScript or JavaScript - SpiderMonkey is an opensource Javascript engine.  This can be embedded into an application and extended with high level application area constructs.  Other embedded scripting tools are available.

The combination of an open source script engine with an object model that is eClinical aware, it is possible to create a syntax that has all the power and flexibility required, while at the same time keeps the complexity of an underlying (potentially super normalized) database hidden.

Value Referencing

This is a key consideration in the definition of a rules syntax.  The inputs and outputs must be easy to reference (readable), non ambiguous and re-usable.  Control of the inputs and outputs is important in order to assure stability of the rules once deployed.   A form of 'black box' approach allows simplified and potentially even automated testing.

Repeatable

Version and Change Management

One of the critical factors in providing an application development solution for EDC is the need to support Version and Change Management - this is a key factor in defining the scripting language scope. Clinical Trials are unusual in that the structure and rules associated with the data may change during the deployment. More import still, the data that may have already been entered may need to be re-applied to the revised structure and rules.  This can prove to be considerably challenging.  If a Study Builder is given total control to add fields, CRF Pages and Visits to an existing study, it would be virtually impossibly to programmatically manage the mapping of data between an old version of a study definition to the new, and still guarantee data integrity.  What this means is that any environment must support metadata release management. In addition, to protect the integrity of regulatory compliance, once data is entered, it must be impossible to delete it even if a protocol change is applied.

Metadata Release Management

Two methods exist for the redeployment of a revised set of metadata against existing data.   You can either only process the changes, or, you can re-apply the existing data to the new definition.  Both methods are workable, but, the latter option can be slow, and requires an extensive and complete object based audit trail containing the former data and actions that can be re-executed against the new metadata.  The former option - to - process changes - requires that the metadata that has been released is managed.  Once data is entered into a system against a set of metadata - the metadata must go into a 'managed' state where all subsequent changes to the metadata can only be re-deployed when it is compatible with the data that has previously been entered.

So - how does this all impact the syntax?

Well, if the syntax is entirely open as far as the actions it performs, and the inputs that it receives, then it is very difficult to handle changes.  On the other hand, if the syntax is limited to operating in a 'blackbox' fashion - for example, comparing datapoints - and returning a boolean followed by the raising of a Query, then the management of a change, or, specifically, the re-execution of the rule against existing data, is predictable.

Lets imagine a large study. It has 1000 rules associated with data.  The study is up and running, and 1,000's of patients have been created.  During the 4th visit, it is discovered that one of the rules defined needs to be changed. The many thousands of other data points, and, rules executed are fine, but, the data points associated with this one rule needs to be changed. The change may effect the previous outcome.  With a combination of managed metadata - where the system is aware of the rule that has changed - and the object based audit trail, it is possible to limit the impact of the change to only the area of the study, and the associated data effected.  This is achieved by only re-executing the actions relative to the changes.

Some Metadata will arrive from an unmanaged source - for example, as an import from an external tool - in this instance, all unmanaged metadata will be assumed to be 'unclean'  and therefore changed.

Rule Actions

So, if a rule executes - by whatever mechanism - and the result of the execution demands an action, what should the action or actions be?   

Some EDC solutions are limited to raising Discrepancies or Queries. Even for the systems that support other actions, Queries, are by far the most common.  However, EDC systems are often differentiated by their ability to offer more advanced forms of actions.

Conditionally adding CRF Pages is one particular action that makes sense.  Changing the status of elements - such as a Subject status might also be useful.

However, one very specific consideration must be supported.  Any actions carried out here may potentially need to be rolled back, or, re-applied as the result of a Protocol update.  Each action that is offered must be fully compatible with the need for re-execution with no adverse results.

Testable

Many eClinical systems fall short when it comes to supporting the full requirements for implementations. In particular, support for testing.  In a strictly controlled, regulated environment, it is as important to prove that a configured eClinical system has been fully tested. The underlying product must be fully validated of course, but, over and above that, regulatory bodies are becoming increasingly aware of the need for configuration testing. 

Good test support in a eClinical 4GL must be built in from the start.  Adding this later is often impossible to achieve well.

To ensure a language is testable, the metadata objects - rules in many cases - need to be managed. The system must keep track of the elements that have been tested, and those that have not.

Speed

The underlying platform probably has a greater bearing on the performance of the 4GL, than simply the syntax.  Also, with web based systems, network latency is an issue.  A potential language needs to be capable of rapid execution. On a typical eCRF it should take less than 50ms to turn around the submission of a page - outside of network latency. Achieving this requires optimization at each step in the execution process.  Extracting data from a super-normalized database - 1 value from 1 record is an issue.  A means to address this is critical.  Avoiding slow interpretation of high level 4GL code is also key.   If the code that is manipulated by the user can be pre-compiled into a more CPU friendly form, then that will help.

Business Aware

Object Orientation

I must admit to being a person that has struggled to get my head around true - or pure - object orientation.  When people start talking about Polymorphism, modularity etc... it all becomes rather cryptic to me. For study developers this could all be too much.

However, I do think that Object Oriented Programming or OOP does lend itself well to specific business problem modelling.  With eClinical, you have certain rules that can be built into objects.  For example, lets imagine we have created an object called a 'Visit'.   A visit can have an attribute 'Name' with values of 'Screening, Visit 1 etc'.  It can also have another attribute 'Number' with values of  '1.0, 2.0 etc'.   Visits could belong to subjects.  Visits can have CRF Pages associated with them.  By defining these 'business objects' and 'object attributes' within the application tool, we can take away some of the complexity of handling relationships and actions from the study programmer.  Instead of having to create a SQL Select inner join between a Visit table and a CRF Form table, the relationship is pre-formed within the application business layer.

So - object orientation - yes, but, only where the resulting user (study developer) experience when preparing studies could be described as 'simple'.

Conclusion

This is all very high level still, but, the above does contain some concepts that may have value in the definition of a potential eClinical 4GL.  In the next posting of the series, we will most likely look at how technologies such as xForms might be supportive in providing an interactive user interface over a web front end to an eClinical 4GL.

Comments welcome!