How to Select & Execute a Biomarker-Driven Clinical Trial Designs

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At the 2016 Duke Industry Statistics Symposium, Dr. Robin Bliss, in collaboration with Dr. Jing Wang of Gilead Sciences, lead a discussion on “Biomarker-Driven Clinical Trial Designs for Precision Medicine.”  Dr. Bliss highlighted two Adaptive Enrichment Clinical Trials performed by Veristat as case studies for how to select and execute an enrichment clinical trial design.

In a world of precision medicine, biomarker-driven clinical trial designs are gaining attention in drug and biological agent research and development.  A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (NIH).  The use of a biomarker-design can improve study efficiency by targeting specific populations and can allow for the focus of research and treatment on each individual patient rather than on an average population.

One subclass of biomarker-driven clinical trials are Enrichment Study Designs.  Enrichment is the prospective use of any patient characteristic (e.g., demographic, physiologic, historic, genetic, etc.) to obtain a study population in which the detection of a drug effect is more likely than it would be in an unselected population (FDA Guidance).  Enrichment designs can be combined with many other adaptive design techniques such as early stopping for futility and efficacy, sample size re-estimation, and focused studies on particular sub-populations of interest.

Many study designs are available for biomarker-driven research, each having different strengths.  The choice of the best study design depends, among other things, on the certainty of the biomarker as a predictive or prognostic factor, the expected difference in mechanism of action and overall effect of the test product among biomarker positive and the overall population, and the prevalence of the disease.  For example, in one case study of a rare oncology trial presented by Robin Bliss at the 2016 Duke – Industry Statistics Symposium, there was some preliminary evidence of a biomarker subpopulation that may impact the effectiveness of the novel treatment; however because the disease was so rare, recruitment in the targeted subpopulation would be difficult.  The study sponsor selected an adaptive enrichment study design which included a planned interim analysis to evaluate the treatment effect in the biomarker positive subjects and the overall population midway through the study.  At that interim analysis, predetermined decision rules were applied to select whether to continue the study with the overall population or with the biomarker positive subjects only.   In a second case study presented by Dr. Bliss, the study sponsor had strong confidence of a prognostic biomarker but was unsure of the treatment performance in the complementary population.   Here, a stratified enrichment study design was selected to allow comparisons between control and novel treatment in both subpopulations of the rare cancer.

These examples illustrate the complexities of selecting the optimal biomarker study design in order to determine a benefit to a biomarker positive or other subpopulation.

 

robin-blissRobin Bliss, PhD is a Manager of Biostatistics at Veristat who helps clients design and manage their clinical trials, both traditional and adaptive designs.   She is experienced working with regulatory agencies, particularly in helping them understand the advantages of applying adaptive designs for biomarker trials.

Veristat Acknowledged for its Rapid Growth on the Inc. 5000 List of America’s Fastest-Growing Private Companies

Inc. 5000

Veristat Acknowledged for its Rapid Growth on the Inc. 5000 List of America’s Fastest-Growing Private Companies

Veristat Continues To Be Recognized for Its Positive Impact & Company Growth

Today we announced that we have been recognized once again by Inc. Magazine as one of America’s fastest-growing private companies. Veristat debuted on the list in 2015.  

“Veristat is proud to have secured its ranking on the Inc. 5000 list for another year.” stated Patrick Flanagan, Chief Executive Officer of Veristat, “It’s an honor to receive this acknowledgement and is proof that Veristat’s passion for helping clients accelerate their life-enhancing and life-saving therapies through the clinical development process is working.  I am proud of the entire Veristat team for working so hard to assist clients every day and exhibiting an unwavering commitment to improving people’s lives.”

Veristat was founded over 20 years ago with a core focus in providing pharmaceutical and biotechnology companies with biometrics, medical writing and strategic regulatory consulting services. Over the past decade and particularly over the past 5 years, the company has expanded into a full-service CRO to help clients design, conduct, analyze and submit the results of their clinical studies for regulatory approval. Last year, Veristat doubled the size of its corporate headquarters and opened its first west coast office to serve our long time clients in the San Francisco Bay area.  

In 2016, Veristat expanded into Europe and now offers the ability to run clinical trials in North America, Europe, and Australia. Additionally, we continued the expansion of our United States footprint with the opening of a Raleigh-Durham office scheduled for the fourth quarter of 2016. We will continue to grow organically and through acquisition to meet the growing needs and demands of our clients.  

Earlier this year, Veristat was recognized as one of the “Top 50 Fastest-Growing Private Companies in Massachusetts” by the Boston Business Journal.   Today’s Inc. 5000 ranking is yet another accolade of Veristat from a prestigious organization that measures and endorses the growth of US companies.

Since 1982, Inc. has ranked the fastest-growing private companies in the United States and published the results on its annual 5000 list. The 2016 Inc. 5000 is ranked according to percentage revenue growth when comparing 2012 to 2015.  To qualify, companies must have been founded and generating revenue by the first week of the starting calendar year, and therefore able to show four full calendar years of sales. Additionally, they had to be U.S.-based, privately held, and independent—not subsidiaries or divisions of other companies—as of December 31 of the last year measured. To learn more and to view the 2016 Inc. 5000 list visit: http://www.inc.com/inc5000/list/2016/.

 

About Veristat

Veristat, LLC is an innovative full-service, science-focused clinical research organization (CRO) with over 20 years of experience in supporting clinical trials and regulatory submissions for pharmaceutical, biotechnology, and medical device companies. Veristat offers comprehensive clinical development services, including biostatistics, statistical programming, medical writing, clinical monitoring and data management, for a single study or an entire clinical program, as well as preparation of integrated summary documents and submission-ready CDISC data for regulatory filings. Due to Veristat’s unwavering commitment to scientific integrity, client focus and exceptional performance, long-lasting client relationships are our hallmark. For more information, please visit www.veristat.com.

 

Veristat Contact:
Gillian Dellacioppa, Marketing Director

Gillian.dellacioppa@veristat.com or 508-306-6336

WHAT ARE THE MAJOR/COMMON TYPES OF ADAPTIVE DESIGNS USED IN CLINICAL TRIALS TODAY?

ADT2An adaptive design is a clinical trial design that allows adaptations or modifications to aspects of the trial after its initiation without undermining the validity and integrity of the trial. An adaptive design consists of multiple stages. At each stage, data analyses are conducted and adaptations take place based on updated information to maximize the probability of success of a trial. In a recent investigation on the use of adaptive trial designs, it was reported that among all adaptive design types that were reviewed:   29% of studies used Group Sequential Design, 16% of studies used Sample Size Re-Estimation, 21% were Phase-I/II or Phase-II/III seamless designs, and 41% were dose-escalation, dose-selection and a mix of others. However, in order to fully understand the advantages of adaptive designs, you have to consider the different types of adaptive designs, their applicable situations, and the so-called operating characteristics, such as average and maximum sample-sizes, early stopping probabilities, and the power.

Let’s quickly explore the common types of trial adaptations which include:

GROUP SEQUENTIAL DESIGN

A group sequential design (GSD) is the simplest type of adaptive design that allows for premature termination of a trial due to efficacy or futility based on the results of the interim analyses (IA).  There are three sub-types of GSDs which are described by their names: early efficacy stopping design, early futility stopping design, and early efficacy/futility stopping design. Statistically, a GSD requires control type-I error, that is the probability of falsely rejecting null hypothesis must be kept below a nominal level.  A GSD may save cost and time due to early efficacy claim at the IA when the treatment effect larger than expected or early futility claim when the treatment effect is much smaller than expected.

ERROR-SPENDING APPROACH

A GSD has to pre-specify at the design stage the total numbers of analyses to be conducted and the timing of interim analyses. This might not be practical due to e.g., the availabilities of DMC (data monitor committee) members.  The Error-Spending Trial design (ESTD) is essentially a GSD, but with the added extra aforementioned flexibilities to allow changes in the total number and timing of the analyses. To control type-I error, an ESTD requires pre-specified error-spending function such that when the timing of the analysis changes, the error-spent at the interim analysis, thus the efficacy stopping boundary will change accordingly. People sometime call ESTD a group sequential design with certain error-spending (e.g., O’Brien-Fleming-like error-spending function). The concept of error-spending can be used in other adaptive designs as well.

SAMPLE-SIZE RE-ESTIMATION DESIGN

A GSD requires the maximum sample size to be pre-specified at the design stage. However, if the treatment effect is under estimated or the interim data show unfortunately low effect, which may cause a trial continuing to the final stage but marginally failed (i.e, p-value just a little over the threshold), we may want to increase the maximum sample size for the final analysis to protect power or conditional power. Such a GSD, featuring sample-size re-estimation at the interim analyses, is called sample size re-estimation (SSR) design.

PICK THE WINNER DESIGN

(also known as drop-the-loser, drop-arm, adaptive dose-finding design,  or Phase II/III seamless design)

Traditionally, Phase-IIB dose-finding and Phase-III confirmatory study are two independent studies. However, a more efficient design is to combine the two studies into one trial, called Pick-the-Winner design (PWD). Such a design if used properly, can reduce the number of patients required and can shorten the duration of the overall development program for the compound.  A PWD is typically a multiple-arm design with two stages: a selection stage and a confirmation stage. For the selection stage, a randomized parallel design with several doses and a placebo group is employed.  After the best dose (the winner) is chosen the patients of the selected dose group and placebo group continue to enter the confirmation stage. New patients are recruited and randomized to receive the selected dose (winner) or placebo. The final analysis is performed with the cumulative data of patients from both stages.

ADAPTIVE RANDOMIZATION DESIGNS

Response-adaptive randomization Design (RAR) is a trial design in which the allocation of patients to treatment groups is based on the responses (outcomes) of the previous patients. The main purpose is to provide a better chance of randomizing the patients to a superior treatment group based on the knowledge about the treatment effect at the time of randomization. A RAR is typically not required to control type-I error. Instead, the determination of design parameters are so optimized to, e.g., minimize the number of failures in the trial.

ADAPTIVE DOSE-ESCALATION DESIGNS

An adaptive dose-escalation design (ADED) is a design in which the dose level used to treat the next-entered patient is dependent on the toxicity of the previous patients, based on some traditional escalation rules. Many early dose-escalation rules are adaptive, but the adaptation algorithm is somewhat ad hoc. Recently more advanced dose-escalation rules have been developed using modeling approaches (frequentist or Bayesian framework) such as the continual reassessment method (CRM) and other accelerated escalation algorithms. These algorithms can reduce the sample-size and overall toxicity in a trial and improve the accuracy and precision of the estimation of the maximum tolerated dose (MTD).

In an ADED, we need to define the toxicity rate of MTD for your disease indication because different designs target different toxicity rate. The typical evaluation matrix for ADED are the sample size, the number of patients with toxicities, and the accurate of predicted MTDs. No type-I error control is enforced.

BIOMARKER-ADAPTIVE DESIGNS

A biomarker-adaptive design is a design that allows for adaptations using information obtained from biomarkers. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacologic response to a therapeutic intervention.  A biomarker can be a classifier, prognostic, or predictive marker each of which have differing effects on the types of adaptations one might plan in the study.  Overall, biomarkers are used at the interim analysis to assist in decision-making, while the final decision will still be based on a primary or gold-standard endpoint, such as survival.

EVALUATION MATRIX OF ADAPTIVE DESIGNS

All adaptive trial designers face a choice among different types of adaptive designs, and the choice of design parameters after determination of a certain type of adaptive design. To make an intelligent choice, the design team has to construct an evaluation matrix and ideally a utility function that combine all aspects in the evaluation matrix into a numerical value. The design corresponding to the maximum utility is the optimal design.

 

READ FULL ARTICLE TO LEARN MORE:

ADTThis list of adaptive designs is not exhaustive but will provide a quick foundation of understanding of the types of adaptive designs commonly used in clinical trials today.

To read more in depth about these types of adaptive designs, when to use them and to explore the opportunities and challenges of each design, read the full article “Adaptive Designs- Recent Advancement in Clinical Trials” by Mark Chang, PhD, Senior Vice President of Strategic Statistical Consulting at Veristat and John Balser, PhD, President and Chief Biostatistician at Veristat.

Biostatisticians: 3 Tips to Knowing When Adaptive Design Is Right for Your Clinical Trial

If you’re reading this as a biostatistician or clinical trial professional, you know that the pharmaceutical industry is shifting from classical to adaptive clinical trial design in an effort to reduce NDA failure rate, lower the cost of research and development, and expedite the precision medicine movement. As a member of the Talent & Culture team at Veristat (a CRO), I spend a great deal of time speaking with people like yourself, many of whom are potential candidates excited about the opportunity to work at a company where they may get exposure to an adaptive design trial. Realizing the consistency across these conversations, I have begun wondering if their interest in adaptive designs is a result of it being a current trends, or if it is because adaptive design truly offers increased efficiencies. As a result, I have spent some time research when adaptive design might not be right for a clinical trial and have found two articles that discuss when it is appropriate to use them.

The first article, titled “Adaptive Design – Recent Advancement in Clinical Trials” was written by Mark Chang and John Balser (in full disclosure, I should tell you that Dr. Chang and Dr. Balser are both members of Veristat’s statistical consulting group), and published last month in the Journal of Bioanalysis & Biostatistics. It focuses on how adaptive design can be a more cost efficient clinical trial approach than the traditional design because it optimizes and streamlines the drug development process. This article also provides a high level overview of the different types of adaptive designs and how to select the appropriate one based on the type of clinical trial. Chang and Balser also review many of the controversies surrounding adaptive trials.

 

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The second article, a discussion between Wade Wirta and Steven Schwager of Medidata Solutions, is titled “When is Adaptive Design Right for your Clinical Trial?” This piece covers similar topics as that of the first article, but leaves out statistical formulations that clarify common confusions among statisticians who have not had a lot of exposure to adaptive trials. Wirta mentions that adaptive trials are not just a change in methodology, but a change in the entire process, including the technology used to run the trial. Additional complexities can be found in operational challenges such as needing a more agile supply chain.

Drawing on these two articles and my conversations with members of the Biostatistics & Statistical Programming Department at Veristat, I have listed three actions that I recommend you take to determine if you should avoid an adaptive design trial:

  • Consider the practicality – Everything from “will the recruitment speed jeopardize the adaptive design?” to “can the interactive voice response system (IVRS) support the adaptive design?”
  • Recognize the complexity – The statistical methodologies for complicated adaptive designs are still being developed, while methods are readily available for more commonplace adaptive designs like futility analysis.
  • Examine the work environment – Adaptive designs only succeed in truly collaborative environments because they require rapid integration of abilities and knowledge from various disciplines into the decision-making process.

Now that you know the challenges posed by adaptive designs, you can go about assessing if an adaptive design in right for your trial. Remember that it doesn’t have to be a complicated adaptation. Perhaps it is as simple adaption such as assessing futility, which is a simple and cost effective adaptation that has the ethical advantage of stopping patient exposure to ineffective drugs.

 

robin-brodrick-head-shotRobin Brodrick is a Talent Acquisition Consultant at Veristat and an aspiring minimalist. Follow Robin on Twitter or LinkedIn for a unique mix of minimalism, job search, and recruiting advice. To learn more about Veristat and its open positions, click here!

What You Missed at the Event of the Year | #DIA2016

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Veristat joined over 6500+ life sciences professionals at the Drug Information Associations (DIA) Annual Meeting  that recently took place in Philadelphia, PA. The conference featured over 175 topics in 25 tracks covering the latest innovations, trends, challenges, and solutions faced by drug developers today. The hottest topics of the meeting were related directly to recent industry trends and events, including increased patient safety, the Zika outbreak, harnessing data to find cures, and many more.

In the exhibit hall, Veristat joined 470 other exhibiting firms who support and offer innovative solutions to improve and accelerate drug development. Veristat was excited to promote its recent expansion into Europe, and to announce its plans to open a new office in Raleigh-Durham, North Carolina. We were also delighted to see many familiar faces along with meeting new ones.

WATCH THE VIDEO

See what you missed at DIA, in our time lapse video of the booth on the last morning of DIA.

LEARN MORE ABOUT VERISTAT

Veristat can help you manage your entire clinical trial, starting with program design, regulatory agency engagement and study start-up activities. We will identify and qualify the top sites for patient recruitment success. Our oversight continues with clinical operations and biometrics services through to regulatory submissions support and agency representation.

We have teams on the ground throughout North America, Europe, and Australia to support your programs.

If you missed the chance to speak with us at DIA or want to learn more, visit us online at www.veristat.com or email us today.

 

Fueled by Growth, Veristat Continues Geographic Expansion

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Veristat announced today that it is continuing its accelerated growth and geographic expansion with the opening of an office in Raleigh-Durham, North Carolina. In addition to this newly planned North Carolina office, Veristat has additional North American-based offices in Southborough, MA, Cambridge, MA, San Bruno, CA, Montreal, Canada, and its European office in Glasgow, UK. The new office, scheduled to open in the fall of 2016, will support the company’s accelerated growth by engaging an experienced talent pool and providing local support to Veristat’s clients in the area.

“Veristat has hired many talented clinical research professionals in North Carolina,” stated Patrick Flanagan, Chief Executive Officer of Veristat. “The Raleigh-Durham area has a population that includes a very experienced and professional CRO community. We have hired and will continue to hire very talented individuals to grow our team of biometrics and clinical operations professionals. Having a local office will facilitate the expansion of our team and allow us to better serve the clinical development needs of our clients.”

Veristat currently has Clinical Operations, Biostatistics, SAS Programming, Data Management and Business Development/Account Management team members based in North Carolina. The Company is currently hiring professionals for all of its business units, including Clinical Operations, Biometrics, Medical & Regulatory and SG&A. Veristat will rapidly accelerate hiring as the office opens later this year. To learn more about open roles, or to apply, visit Veristat’s Careers page at http://www.veristat.com/careers/.

About Veristat:

Veristat is an innovative full-service, science-focused clinical research organization (CRO) with over 20 years of experience in supporting clinical trials and regulatory submissions for pharmaceutical, biotechnology, and medical device companies. Veristat offers comprehensive clinical development services, including biostatistics, statistical programming, medical writing, clinical monitoring, project management and data management, for a single study or an entire clinical program, as well as preparation of integrated summary documents and submission-ready CDISC data for regulatory filings. Due to Veristat’s unwavering commitment to scientific integrity, client focus and exceptional performance, long-lasting client relationships are our hallmark.

 

Veristat Strengthens Statistical Consulting and Adaptive Design Trial Expertise

Veristat Strengthens Statistical Consulting and Adaptive Design Trial Expertise

Appoints Mark Chang as Senior Vice President of Strategic Statistical Consulting

 

We are proud to announce that we have strengthened our statistical consulting and adaptive design expertise with the appointment of Mark Chang, PhD to the newly created position of Senior Vice President of Strategic Statistical Consulting.   Dr. Chang will help clients evaluate and implement strategic, operational and technical efficiencies to advance products through the clinical trial and regulatory submission process.

“Veristat is thrilled to welcome such an esteemed clinical research and statistical expert to Veristat,” stated John Balser, PhD, President of Veristat. “Mark will provide Veristat’s clients with the intellectual leadership to optimize their clinical development plans, trial designs and regulatory submission strategies.  His experience with designing and implementing both simple and complex adaptive design trials is unmatched in the industry.”

Mark ChangDr. Chang joins Veristat with more than 20 years of experience as a statistician at both biopharmaceutical firms and CROs, including AMAG Pharmaceuticals, Millenium/Takeda Pharmaceuticals, PAREXEL and MTRA.  He is experienced with NDA submissions and working collaboratively with the regulatory agencies throughout the clinical trial and submission process.  Dr. Chang is also an adaptive design expert, having authored and co-authored dozens of books and peer- reviewed journal publications on adaptive design methodologies and implementation in clinical trials.

In addition, Dr. Chang is a fellow of the American Statistical Association and an adjunct professor of Biostatistics at Boston University.  He is a co-founder of the International Society for Biopharmaceutical Statistics, co-chair of the Biotechnology Industry Organization (BIO) Adaptive Design Working Group, and a member of the Multiregional Clinical Trial (MRCT) Expert Group.  Throughout his career, he has frequently held advisory posts for numerous industry committees and served as an associate editor for many peer-reviewed publications.  He has given over 50 lectures, short courses, and invited speeches at national and international conferences and has been invited twice to present at the US Food and Drug Administration.

Dr. Chang received his Ph.D. in Civil Engineering and his Masters of Science in Biostatistics at the University of Massachusetts in Amherst, MA.   He also received his Masters of Science and Bachelors of Science degrees at Hohai University in Nanjing, China.

 

About Veristat:

Veristat is an innovative full-service, science-focused clinical research organization (CRO) with over 20 years of experience in supporting clinical trials and regulatory submissions for pharmaceutical, biotechnology, and medical device companies. Veristat offers comprehensive clinical development services, including biostatistics, statistical programming, medical writing, clinical monitoring, project management and data management, for a single study or an entire clinical program, as well as preparation of integrated summary documents and submission-ready CDISC data for regulatory filings. Due to Veristat’s unwavering commitment to scientific integrity, client focus and exceptional performance, long-lasting client relationships are our hallmark.  For more information, please visit www.veristat.com.

 

Veristat Contact:
Gillian Dellacioppa, Marketing Director
gillian.dellacioppa@veristat.com or 508-306-6336