Think Tomorrow – Clinical Development Revolution

Think Tomorrow – Clinical Development Revolution

It is common to utilize medical imaging in clinical trials across most therapeutic areas to monitor safety and efficacy of a new therapeutic drug candidate. However, it is often forgotten that the choice of the right endpoints will not only lead to go / no go decision but really is critical to any future developments of the clinical assets as well as financial health of the entire company.

Successful design and execution of a clinical study can enable getting efficacy data as early as phase I, getting phase 3 terms while still in phase 2 and can lead to an early asset acquisition even before the study completes.

For a biotech company, the several key aspects which should be thought through at the very start are:

1) benchmarking your asset development path, MoA, its strengths and weakness against the assets in failed or successful deals in similar TA and the appetite of pharma players in this TA;

2) choice of the right analytics to reflect the efficacy objectively, adequately and early;

3) thorough assessment of the risks, including recruitment, site capabilities, regulatory barriers to approval, costs and timelines.

Imaging is the critical trial de-risking mechanism when it comes to the competitiveness of the data, objective early efficacy and patient retention.

We always compare ourselves to the other people’s data.

When we design a trial, it is easy to rely on the publicly available data, expertise of our scientific advisory board and www.clinicaltrials.gov.

It is often underestimated that we need to compare the yet to-be-developed asset to the future investor expectations.

This task is difficult because there is no clear path of getting to the right answer. It is easy to look at what has been done, in terms of efficacy and efficacy endpoints 10-20 years ago and just do the same. Not surprisingly, this is not a winning strategy.

With the latest developments in imaging modalities, AI and machine learning, we are living in the era of unprecedented precision, patient phenotyping and early efficacy focused radiomics. It is risky to rely on the past experience along and not think 3 steps ahead.

A clear strategy to enhance efficacy can lead to earlier approval or / and asset acquisition.

 

A case study built with one of our portfolio companies can be found here: http://www.ia-grp.com/case_studies/clear-strategy-to-enhance-approval-led-to-the-asset-acquisition-before-the-phase-ii-study-was-complete/

Patients is the reason we are in this business.

But developing a universal unicorn treatment is too risky, even for a big pharma, let along the ambitious but budget constraint biotech companies.

There is tremendous inter-patient variability in the response to even highly efficacious treatments. This is a great source of frustration for our clinicians, which led to development of “precision medicine” or more precisely empirically based algorithms that determine the optimal treatments or treatment combinations for individual patients that would improve both the clinical care of patients and the success rates for drugs in phase 2 and 3 clinical trials.

However, this approach will only succeed if the characteristics of individual patients or subgroups of patients that influence the response to a specific treatment are identified and utilized effectively.

The challenge is to identify the *measurable* phenotypic characteristics of patients that are most predictive of individual variation in treatment outcomes, and the measurement tools that are best suited to evaluate these characteristics.

Imaging is the component for a subjective opinion free assessment and should be used at the very start, at the design stage of the trial and gold-thread through the entire process of the clinical development, ensuring that we are still objective in any decisions and not relying on patient or clinician reported outcomes exclusively.

Another case study with our portfolio company can give some further food for thoughts: http://www.ia-grp.com/case_studies/20-reduction-in-trial-length-by-deploying-the-optimized-patient-stratification-approach/

 

Using Cloud is the Norm

Imagine reading this just 3-5 years ago. The first reaction would be – is this secure? I don’t want to send my data to the cloud? Where is this cloud anyway? Is this compliant….

Now, it is the norm. If today you attempt to send your MRI data by CD or email…then you most likely working with the wrong partner and probably should check the data protection regulations as soon as.

Think of 3-5 years from now. AI, Machine Learning, Radiomics, imaging biopsy like tests, Big Data Analytics, Regression analysis, decision support mechanisms, image registration, segmentation, Bayesian neural networks and many other pure maths terms will be the norm.

Every study we run, we begin with integrating data flows to ensure interoperability of disparate systems and integration of data sources.

DYNAMIKA, our unique cloud data management platform and probably some other systems should be there to eliminate data silos by continually harnessing all of the information in a trial from all of the data sources — sites, investigators, previous trials, sub-studies.

More importantly, the data is consolidated, reconciled and single-view reported as valid information to the study team on an ongoing basis.

After unlocking the insights that disparate data sources collectively contain, sophisticated analytics are used to interpret the information, drive fact-based decisions and reduce prevalent risk factors in clinical studies.

If this sounds futuristic…it is not, this is the new modern way of thinking about the trials!

Just as an example, in many of our latest studies, we automate a complex patient eligibility calculation after aggregating live data from multiple disparate data sources in order to immediately decide the right patients to enrol in a study.

In rheumatology trials, we bring together imaging scoring systems to correlate them to histology and make sure the patient’s pain is no longer a hidden undefined variable.

In oncology, we can predict overall survival in ½ the time of the trial length through the advanced imaging.

This is changing our understanding of the disease and patient response. This is changing the guidelines and therefore the future of the trials.

What important today that in any sensible trial there is a platform which plays the critical single point of access and analysis of live data from numerous internal and external information systems. We can then deal with the data. And there is never enough data to answer all the questions!

 

It is my personal believe and our company’s passion that a bio-pharma company should be able to make early informed decisions while conducting the study based on the customized reports, including a trial performance, trend monitoring, analytics dashboards and real-time accessible and informative assessment by multitude of experts.

Imaging is the pulse of the study!

We can see and measure the treatment efficacy, but at the same time we can create a feedback loop to the sites and local PIs giving them baseline data to motivate patients or to monitor someone on the high risk treatment trial. Imaging in this case would help maximizing clinical outcomes and chances of success through more efficient patient retention and faster decisions.

For over 10 years, we helped our bio-pharma partners to overcome the challenges to successful drug development and achieved unparalleled business results by transferring our scientific expertise, operational practices and technology innovation to their organizations.

We understand that each trial needs to deliver scientifically credible data, which is often pivotal to any future developments of your assets as well as financial health of the company.

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