Statistical Approach to COVID-19 Clinical Trials Aims to Accelerate Drug Approval Process

In response to the COVID-19 pandemic, researchers from the Massachusetts Institute of Technology have published a pair of studies in a COVID-19 special issue of the Harvard Data Science Review, freely available via open access, describing new methods for accelerating drug approvals during pandemics and for providing more accurate measures of the probabilities of success for clinical trials of vaccines and other anti-infective therapies.

"Randomized clinical trials - where patients are assigned randomly to two groups, one receiving a new treatment and the other receiving a placebo or reference treatment - are the gold standard for determining the safety and effectiveness of a treatment," says Andrew Lo, Ph.D., the study's senior author and the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management. "Only when the treatment group shows significant improvement over the control group, will regulators approve the therapy." He adds, "the current process is designed to protect the public by minimizing the chances of "false positives" (approving ineffective and unsafe therapies), and by and large, it's been very successful."

But there is a trade-off between false positives and false negatives (not approving a safe and effective therapy), and Lo and his collaborators have developed a framework that uses an epidemiological model of COVID-19 to calculate the optimal statistical threshold for approving a drug during a pandemic. "In the midst of an outbreak, many lives are at stake so we need to be less concerned about false positives and more concerned about false negatives than during normal times," says Lo, "In response, we've developed an analytic framework that allows regulators to make this trade-off systematically, transparently, and rationally."

At the core of this new framework - which was jointly developed in collaboration with MIT students Qingyang Xu and Danying Xiao, and former MIT student Shomesh Chaudhuri, Ph.D. (now at QLS Advisors) - is an explicit optimization algorithm designed to minimize the expected loss of life across various scenarios generated by a statistical model of an infectious disease. This algorithm, says Xu, will lead to more drug approvals during outbreaks, not unlike the U.S. Food and Drug Administration's Emergency Use Authorizations (EUA) program. "Our framework complements the EUA, allowing regulators to incorporate loss-of-life considerations quantitatively during periods of extraordinary stress," explains Xu, the lead investigator of the study.

In a companion study authored by Lo and MIT Ph.D. students Kien Wei Siah and Chi Heem Wong, the MIT researchers estimated the probabilities of success (PoSs) of clinical trials for vaccines and other anti-infective therapies using the Citeline® dataset provided by Informa Pharma Intelligence, part of UK-based publishing company, Informa®. This dataset includes 43,414 unique triplets of clinical trial, drug, and disease over the past 20 years, yielding over 2,500 vaccine programs and more than 6,800 nonvaccine, anti-infective programs, the largest dataset of its kind.

"The PoS is a key input into each major decision of every biopharma company about which disease to tackle and how much resources to devote to it," observes Lo.

Because a successful clinical trial can mean billions of dollars in revenues, small changes in PoS can lead to very different business decisions. Therefore, having timely and accurate measures of PoS is critical - and often, these better measures of risk and reward allow investors to put more capital to work.

The overall estimated PoS for industry-sponsored vaccine programs is about 40%, which is the highest among all disease groups (by comparison, the PoS of cancer trials is, historically, less than 5%), and 16.3% for industry-sponsored nonvaccine, anti-infective programs. Viruses involved in recent outbreaks--Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS), Ebola, and Zika--have had 45 nonvaccine and 35 vaccine development programs initiated over the past two decades, and there have been only two approved vaccines to date (for Ebola). This points to a clear need for new policies to address this gap.

"As governments around the world begin to formulate a more systematic strategy for dealing with pandemics beyond COVID-19, these estimates can be used by policymakers to identify areas most likely to be underserved by private sector engagement and in need of public sector support," said Wong, the study's lead author. These results are part of Project ALPHA (Analytics for Life-sciences Professionals and Healthcare Advocates) - an ongoing initiative at the MIT Laboratory for Financial Engineering (LFE) where Lo is director - to help make the biomedical funding ecosystem more efficient. "We now provide this information on a regular basis, it's not just a one-shot deal," Lo says. Users can obtain the most current PoS estimates at https://projectalpha.mit.edu.

Shomesh Chaudhuri, Andrew W Lo, Danying Xiao, Qingyang Xu.
Bayesian Adaptive Clinical Trials for Anti-Infective Therapeutics During Epidemic Outbreaks.
Harvard Data Science Review, 2020. doi: 10.1162/99608f92.7656c213

Most Popular Now

Virtual Reality could Help to Reduce Pai…

We all feel physical pain in different ways, but people with nerve injuries often have a dysfunctional pain suppression system, making them particularly prone to discomfort. Now researchers have uncovered that...

Early Warning System for Intensive Care …

Life-threatening situations occur time and again in an intensive care unit. To make sure that doctors can intervene in time, a team at the German Heart Center Berlin (DHZB) has...

Philips Partners with Orbita to Develop …

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Orbita Inc., an innovative provider of conversational artificial intelligence (AI) solutions for healthcare, announced a partnership agreement...

CliniSys Group Creates Single Brand for …

CliniSys Group has created a single brand for its businesses in the UK and Europe, with a refreshed logo and a new website. The move creates a unified identity for CliniSys...

East Lancashire Signs Deal for Early War…

Thousands of NHS professionals across five hospitals in East Lancashire are to benefit from early warning technology that will help them detect and swiftly respond to deteriorating patients in need...

FDA Grants Oxehealth Vital Signs De Novo…

Oxehealth has announced another world first after the US Food and Drug Administration granted a De Novo clearance for its Oxehealth Vital Signs product, which is incorporated into Oxevision, the...

Telemedicine Improves Access to High-Qua…

The American Academy of Sleep Medicine recently published an update on the use of telemedicine for the diagnosis and treatment of sleep disorders to reflect lessons learned from the transition...

DMEA 2021: Digital Health. 100 % Virtual…

7 - 11 June 2021, Berlin, Germany. An entire week dominated by digital healthcare! With that in mind, early in June DMEA 2021 will be kicking off with a wide range...

Philips and NHS Implement the First Regi…

Royal Philips (NYSE: PHG, AEX: PHIA), announced it has supported the NHS' Cheshire and Merseyside consortium [1] to become the first regional hub supplying the United Kingdom's National COVID-19 Chest...

Child Brain Tumours can be Classified by…

Diffusion weighted imaging and machine learning can successfully classify the diagnosis and characteristics of common types of paediatric brain tumours a UK-based multi-centre study, including WMG at the University of...

AI could Crack the Language of Cancer an…

Powerful algorithms used by Netflix, Amazon and Facebook can 'predict' the biological language of cancer and neurodegenerative diseases like Alzheimer's, scientists have found.