The Two Biggest Barriers to Bringing New Drugs to Market
If COVID-19 has done anything well, it has exposed holes in the care continuum. Timelines to improve outcomes are too long and too costly. This pain is felt the most in the development and deployment of new pharmaceuticals, therapeutics, and vaccines.
A recent study by Tufts University, Duke University, and the University of Rochester published in the Journal of Health Economics, stated that developing a new drug was estimated to cost drugmakers $2.6 billion. Additionally, it takes at least 10 years to get a new drug to market. This was a best-case scenario when the world was “normal” and not wrestling with a global pandemic.
COVID-19 has provided us a stark reminder that corporations will need to look towards digital innovation in order to decrease the time and cost to market.
Specifically in pharma, we believe the bulk of wasted time and costs are lost within traditional Drug Discovery and Trial processes.
Drug Discovery
The traditional process of drug discovery involves the identification of new drug candidates, synthesis, characterization, screening, and assays for therapeutic efficacy. Historically, this process requires an immense amount of wet chemistry leading to exorbitant costs.
Years of research and development in conjunction with publicly available information has created novel datasets that can be leveraged by technologies like artificial intelligence (AI) and machine learning (ML) to rapidly decrease the time to discover new drugs and vaccines.
COVID-19 has put pressure on big pharma to develop new treatments and has highlighted deficiencies in the process overall. Because of this, companies are now looking at existing drugs in the market to target diseases, a process called repurposing. Similarly, AI and ML can be used to increase a company’s ability to leverage their existing portfolio of drugs to find matches.
So, why are companies in a rush to repurpose? Repurposing drugs, especially your existing portfolio, is faster and less costly. It’s estimated that 10% of new molecules get to market from Phase II clinical trials and 50% from Phase III. However, the rates for repurposed compounds are 25% and 65% respectively. Furthermore, depending on what trial data exist, repurposing a drug can reduce the need for additional trials, cutting 10-15 years and $1-$2B in costs out of the process when bringing a drug to market.
Preclinical and Clinical Trials
Preclinical trials are the beginning step in turning theory into practice. Clinical trials take this one step further. The fundamental purpose of a clinical development program is to tell healthcare providers and patients how to use the drug effectively and safely.
Coordinating trials is like conducting an orchestra. Trials must be designed, tested, and evaluated. In this complex process, inefficiencies permeate. Labs conducting preclinical trials often work in silos and perform redundant experiments, while poorly designed clinical trials recruit non-optimal patients and have poor response to therapies.
Leading edge technologies like AI can be used by companies to increase the likelihood of success and reduce waste in trials. Intelligent lab and study management software allows for distributed information sharing and collaboration across multiple sites, reducing duplication of efforts and increased process control.
Roughly 80% of delays in clinical trial timelines are accounted for during patient recruitment and retention. In a study conducted by the U.S. Department of Health and Human Services (HHS), patient recruitment costs make up more than 25% of the overall trial costs, totaling an average of $805,785 for trial phases 1 to 4. While patient retention (mainly through patient assistance programs) is only about $76,879, or 9% of the overall clinical trials’ costs. AI can also be leveraged to predict better responders to a therapy and improve patient recruitment, leading to more efficient trials and reduced costs.
We are not too naive to think that these problems didn’t exist pre-COVID-19. However, if anything, COVID-19 has acted as a catalyst for change by surfacing the hard truths that we knew existed, but were pushing off.
Companies who do not embrace and incorporate the bleeding edge of technology into their ecosystem will be disrupted by external forces. This is why Nex Cubed has invested in companies like Repurpose.AI, Trials.ai, and RockStep Solutions who are tackling these hard truths head-on.
Daniel J. Haders II, Ph.D. is the Managing Director of Nex Cubed Digital Health and an Operating Partner at Sway Ventures. Nick Phillips is the Program Manager of Nex Cubed Digital Health.