Game Changer: How Genomics and Technology are Transforming Clinical Trials

Innovation That Matters

Advances in genomics are improving elements of drug development, such as design of clinical trial protocols, enrollment of patients and measurement of a potential drug’s effectiveness, but drug development still takes too long, is too expensive and too few drugs ever get approved.

“When you look at the available technology, the breakthroughs with biomarkers and genomics, it seems logical that we should be able to reduce the time and cost of drug development,” says John Farinacci, General Manager, WuXi Clinical Development Services (USA), Inc., formerly ResearchPoint Global (RPG). “As much as I wish I could tell you that is the case, there is no documented evidence out there to support that at this stage.”

However, Farinacci expects genomics eventually will accelerate drug development, reduce overall cost and improve outcomes industry-wide. He notes the science already is producing more effective treatments for patients. But in the near term, he says, the tech sector is likely to have the greatest impact on clinical trials “from advances in artificial intelligence, block chain, cloud computing and big data analytics.”

Farinacci founded RPG in 1999 and the Austin, Texas-based contract research organization (CRO) was acquired by WuXi AppTec in 2017. He has 45 years of experience in clinical drug development, having also served as Executive Vice President of Quintiles Transnational Corp. and president and chief operating officer at Pharmaco (currently PPD). Farinacci earned his degree in biology/chemistry from New York’s Russell Sage College.

In a recent interview with WuXi AppTec Communications, Farinacci discussed the ongoing changes in the clinical trial process and the many challenges of bringing new drugs to patients worldwide.

WuXi: How have clinical trials evolved in the genomics era? What are the improvements?

John Farinacci: There definitely have been changes in clinical trials in the past decade, especially in trials that deal in the treatment of oncology. The original focus was more from an organ-based perspective. Now it has moved more to a genomic based We recognize and continue to identify genes that cause or contribute to  certain diseases and thus are important in enabling more accurate diagnoses, and specific treatments.

Overall, the basic improvement is having the ability to differentiate between patient responders and non-responders in the earlier trials to help reduce the sample size and improve the efficiency in later trials.

WuXi: How is CDS applying new technologies in clinical trials? What are some of your major advances and how are they improving outcomes?

John Farinacci: We are not a technology company, but we pride ourselves in being able to take advantage of technologies that are available. Like many other companies we are taking advantage of technologies such as wearable devices, electronic data capture, electronic patient reported outcomes, otherwise known as ePRO, and imaging to improve the quality of clinical trials through improved patient compliance as well as, data collection, tracking, and reporting methods.

We have begun to focus more on genomics by taking advantage of our sister company, WuXi NextCODE, a fully integrated contract genomics organization, in partnering to provide clients a genome-based development solution to reduce cost, time and risk as well as improve treatment response.

We are determining, particularly in the area of oncology, which is currently one of the leading areas of clinical development, how can we better identify and target the  most likely to benefit populations for a given clinical trial to ensure a response rate that will better serve our clients in getting their product to market much faster.

WuXi: How have Phase I trials changed? Have they become more than the traditional escalation, safety trials? How do you find the right patients?

John Farinacci: Traditionally, the initial Phase 1 trial is a safety trial in normal healthy volunteers. Usually you find these volunteers in larger, densely populated cities and/or college towns. Sites actually draw from data bases of professional healthy normal volunteers they have developed over time.

However, with the rapid growth in the number of products being investigated in oncology and rare diseases, the approach is a little different because we’re trying to get to the market place much faster and get to a decision point much quicker. So, you’re looking at more comprehensive and complex Phase 1-type trials, whose focus is beyond safety, incorporating efficacy and outcome endpoints.

These trials involve actual patients, so much like in Phase II & III trials, there is a lot of competition for patients, and it’s much harder to find the specific patients who meets the inclusion and exclusion criteria. We do a lot of feasibility work in selecting the right sites. We also have affiliations with specialized Phase I sites as well as with academic and commercial clinical trial sites. We also have experienced staff and medical personnel who help with our site selection process.

WuXi: Can the length of time it takes to conduct clinical trials and the cost be reduced? If so, how?

John Farinacci: When you look at the available technology, the breakthroughs with biomarkers and genomics, it seems logical that we should be able to reduce the time and cost of drug development.

However, the time from lab to shelf is still around 12-to-14 years at a cost of approximately $2.6 billion. Why? There are a number of reasons, but I believe there are a few that can best explain it and put it in proper perspective.

Earlier we talked about genomics, and the impact it can have on finding the right patients, but when you incorporate genomics – genetic data – into a trial, it can significantly increase the amount of data points collected and analyzed per patient by five or 10 fold.  In recent years, the number of trials continues to increase, resulting in more competition for patients, particularly in sectors where there is a higher mortality/morbidity rate. So, there is cost associated with additional feasibility and patient recruitment.

Then there’s a cost associated with advancing technology, licensing and support. We talk about all these advances and their incorporation into the clinical development process, but the time it takes to get a product to the marketplace is still quite lengthy and very expensive. But I do believe the types of products that we are getting to market are better, more effective, and are improving and saving lives.

WuXi: What role are biomarkers playing in improving clinical trial outcomes?

John Farinacci: Biomarkers not only improve the accuracy of diagnosis, but biomarker enabled clinical trials appear to have a higher success rate.

I recently read an article that said the proper incorporation of biomarkers in an oncology trial could increase the likelihood of approval by 10% to 25%. When you think about the success rate of drugs that go from an IND to market approval, only 10% of those drugs make it. Of all INDs filed, only 11% ever hit the marketplace. So just think, if you could increase that by an additional 25%. That’s pretty substantial.

Biomarkers can also serve as secondary and supplemental outcomes. But much more work needs to be done to better understand how to utilize that technology to identify biomarkers and link them to the clinical measures of a particular disease.

We’re making great headway, but our industry tends to be a bit more behind the curve when it comes to technology as compared to the financial community and other industries

WuXi: How is adaptive trial design applied? Can it reduce clinical trial failures?

John Farinacci: Basically, adaptive design is used to increase the efficiency and accuracy of clinical trials by emphasizing strategies that help find treatment groups that are responding well; and then on the other hand, reduce treatments that don’t respond well. This is all planned carefully in the development and statistical plan so that it never undermines the statistical validity of the study outcome.

Can adaptive trial design be used to reduce failures? It can be used to identify “failures” early. However, it does not reduce the number of product failures. It eliminates them earlier in the process. So, you will still have studies that fail, but you should be able to reduce the number of late stage failures.

There are many different types of adaptive trial design. A very common one is for a sample size re-estimation, which is pretty self-explanatory. Another one has a very interesting name – it is called ‘either ‘pick the winner’ or ‘drop the loser’ design that is often used for dose selection. It’s been used to combine a Phase 2b study with a Phase 3. A Phase 2b study is a study that’s often done to help identify or select the optimum dose for treatment. The Phase 3 study, 99% of the time, is a confirmatory study. The studies start enrolling altogether, but early on you’re able to identify the best responsive group within that Phase 2b component. You select that group and move forward with the Phase 3 component.  As a result, you don’t have to run a full-blown Phase 2b study, which could take one or two years depending on the trial, followed by writing up the results and then rolling out your Phase 3. You can do them in conjunction, so to speak.  There are also opportunities to include biomarkers in the adaptive process by testing whether the biomarker actually can predict outcome and if so, continue only with patients with the biomarker of interest.

WuXi: What role should patients play in clinical trial design?

John Farinacci: The thing that really stands out, if you look at a few metrics that are out there about studies – such as what are the biggest rate limiting steps in meeting timelines – there’s about three that really involve the patient.

One is that 80% of clinical trials fail to meet enrollment timelines. Another one is that 50% of the sites enroll one or sometimes no patients. We have a rule of thumb internally when we are trying to decide on the number of sites we should use; historically 80% of the patients come from 20% of the sites.

The last metric that estimates about 5% to 7% of available patients participate in clinical trials I think is very telling and will be the driver in looking at solutions to get more patients involved. It is obvious that if getting patients in clinical trials is a rate limiting step, we have to figure out how to have patients become part of the solution to make it work.

There was a survey conducted of patients and the first thing that surfaced was that simplifying the study logistics was at the top of the list for patients when considering participation in a trial. Other points that came up were the number of blood draws and transportation because of the frequency of visits back to the facility. The survey group also asked: ‘Is there a way I can incorporate my mobile device, my phone, my iPad?’ How can we get appropriate data from the patient without the burden of site visits?

Finally, patients who participate in clinical trials want to be taken into account and want to know the results of the study that they participated in. And the biopharmaceutical industry has not been very good at this. It has been shown that when the results of a clinical trial are shared with those who participated in the study, the incidence of repeated participation in subsequent trials is higher for those patients.

From my perspective, it’s doubtful that patients will ever be allowed to totally drive a clinical trial from a medical perspective, however, I believe we need to start paying attention to the views of the patients and have them become partners and part of our team in designing and in sharing the results of our clinical trials.

WuXi: What are some of the major differences in conducting clinical trials in the US, Europe and Asia?

John Farinacci: Other than language differences, which are going away as more and more people are conversant in English, there is very little difference in the basic conduct of a clinical trial globally.

But there are specific regulations and laws that govern clinical trials in host countries that must be adhered to. So, it is imperative that a sponsor become familiar with a country’s specific regulations and registration laws.

They also have to understand the timelines are much different and understand the standard of care varies from country to country.

There are laws about how you import-export clinical investigational products. There are laws on how you handle clinical samples and specimens, getting them in and out of the country. Each country has its differences and even within the European Union (EU) there are still variances.

There’s another item that got thrown into the equation recently, and that’s the EU’s adoption of the General Data Protection Regulation (GDPR), which diligently protects personal European data globally. It requires another level of documentation. It’s not only within Europe. If you’re interacting or doing anything with European data, you need to be able to document that you comply with the GDPR code.

There are two other items that come into play. Price is often one of them, but what I most often see as a concern for clients is “time”. Every country is a little bit different in the time it takes to get Competent Authority and Ethics Committee approval and to trial initiation. So, it typically takes longer than US clients may be accustom to, but the wait is often worth it. China and Eastern Europe countries have large patient populations to draw from and the quality is very good.

WuXi: What will make a difference in reducing the time and cost of clinical trials? What changes do you foresee in the clinical trial process over the next five years?

John Farinacci: Genomics and adaptive approaches to accelerate development timelines and market penetration will have an impact. However, I believe the greatest impact will remain to be seen with the advances in artificial intelligence, block chain, cloud computing and big data analytics.

A recently published article showed how Google technology could help physicians better diagnose disease and predict outcome.  It is very impressive because they were able to sift through data from medical notes buried in files; medical records with notes scribbled on old charts and in corners of margins. I don’t know exactly how they did it but they were able to present the predictive information far faster and more accurate than existing techniques today.  The next step would appear to be going into clinics and clinical trials with this technology.

Currently, patient identification, recruitment, screening, and enrollment remains one of the most challenging and time-consuming components in clinical trials. By taking advantage of this technology and available tools, the impact it could have on shortening timelines and getting products to the marketplace faster could be significant.












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