
TCEM and NAMs: An Innovation Superhighway for Drug Development
By Andrew C. von Eschenbach, Ralph F. Hall, and Mark Hendrickson
Stakeholders, including FDA, agree that we urgently need to accelerate and reduce the cost of developing new drug therapies without lowering safety and efficacy standards. Today, the road from identification of a promising molecule in the laboratory to a marketable drug is long and arduous. However, there is hope on the horizon; new tools referred to as Technology and Computational Evidence and Modeling (TCEM) New Approach Methods (NAMs) can turn this laborious process into a “superhighway.” While many phases of animal and human testing can be improved, perhaps the greatest opportunities for improving the development of new drug therapies come from innovative, non-clinical tools—if we can seize them.
Current Status
Currently, innovative pharmaceutical products are developed using a three-phase research and development (R&D) process: bench studies, preclinical studies (i.e., animal research), and human clinical studies.
Despite ongoing efforts to improve preclinical and human studies, the time to develop a new drug is approximately nine years, notwithstanding spending increases in R&D.[1] Developer spending on R&D, including capital costs and the cost of drugs that fail to reach the market, is estimated to range from $1 billion to more than $2.4 billion per new approved drug. In 2019, larger research-oriented drug companies spent $83 billion on R&D—approximately 10 times the amount spent in the 1980s and twice the amount in 2000. The bulk of these costs are incurred in the human clinical trial stages.[2]
To make matters worse, despite best efforts, most drug candidates fail for safety or efficacy reasons. Only about 1–2% of drugs that enter animal studies receive FDA approval.[3] These failed molecules consume time, add costs, and redirect resources from promising targets. This cannot continue.
The Need for Speed
We need faster, more successful, and lower-cost R&D processes to bring new therapies to patients at reasonable costs, without lowering our safety and efficacy standards. Unfortunately, further improvements in current preclinical and clinical research processes alone are not going to get us there. New and better nonclinical tools are the keys to better new drug research in the future.
Imagine researchers using a tissue-on-a-chip technology to grow human tissue for laboratory testing instead of testing therapies on mice. This technique could replace years of costly animal research that often fails to predict human response, particularly toxicity. For example, researchers at Columbia University used innovative human tissue platforms to test vascular, liver, and cardiac tissue to assess drug effectiveness and toxicity.[4] Advanced computer modeling can both develop new, targeted molecules and identify drug/drug interactions. These and other nonclinical technologies can often provide faster, lower cost, and more accurate assessments of new drug therapies.
Because people are not mice, while animal testing is used to predict the effect (be it positive or negative) of a compound on humans, animal models remain a rough approximation of human biology. We all remember Vioxx, which unfortunately increased risk of cardiovascular morbidity and mortality not detected during animal studies. This is common—about 88% of drugs that “pass” animal testing fail human studies.[5] Michael Leavitt, then U.S. Secretary of Health and Human Services, stated, “investigators are increasingly concerned that animal experimentation may be based on a scientifically flawed premise and that it retains its acceptability only because clear alternatives have not been identified.”[6]
Human studies are even more time-consuming and expensive than animal studies. Despite process improvements in human clinical testing, time frames and success rates have remained steady, and R&D costs continue to increase year-over-year.[7]
The bottom line is that improvements to preclinical animal study and human clinical study processes have not bent the time–cost curve for new therapies. We need to adopt a better approach.
Solutions are Within Reach
Fortunately, technology is providing new and increasingly powerful levers that we can use to accelerate patient access to safe and effective new therapies.
These powerful new technologies include AI, silico-based techniques (i.e., “tissue or organ on a chip”), new statistical tools, and computational modeling. These and other new technologies and tools, generally referred to as Technology and Computational Evidence and Modeling (TCEM) or New Approach Methods (NAMs), can provide:
- More accurate ways to identify promising drug candidates.
- Methods to design faster and more responsive clinical trials.
- Faster shelving of targets that show a low probability of success.
- Faster identification of safety and efficacy issues.
- Tools to test new drugs with better safety and efficacy profiles.
- Methodology for better utilization of real-world data/real world evidence.
TCEM and NAMs have the potential to identify promising new molecules faster, cheaper, and more accurately. For example, computational modeling can help identify potential drug/drug interactions, search large databases for safety and efficacy information, more readily identify cures for rare diseases, advance repurposing of older drugs, and help create new molecules.
In summary, TCEM and NAMs present faster, lower-cost ways to identify promising new drugs and focus our research efforts, before we spend the time and money on costly and risky animal and human studies. By using these new tools, patients get access to safe and effective new drugs faster and cheaper, without lowering our approval standards.
A Call to Action
Patients need faster and lower-cost access to safe and effective drugs—and TCEM and NAM tools offer a path forward to achieve these goals. Harvesting the benefits of these new technologies requires engagement and commitment from all stakeholders: industry, FDA, researchers, academics, patients, and Congress. These stakeholders need to collaboratively develop TCEM and NAM tools and, importantly, to maximize their regulatory uses. This is an achievable goal if stakeholders work together.
For these tools to succeed, we need increased support from Congress, FDA engagement, industry commitment, advanced research, and patient support to fine-tune, validate, and standardize these technologies. We need regulatory alignment and modernized guidances, including new recognized standards and advanced processes at FDA and other regulatory agencies, such as the European Medicines Agency. These actions require a commitment from all stakeholders to advance the use of these tools for the ultimate benefit of patients.
Conclusion
FDA, industry leaders, academics, researchers, standards developers, patients, and Congress must unite to support the development and use of TCEMs and NAMs to speed patient access to innovative, safe, lower-cost life-saving therapies down the superhighway. The current product development model must evolve and embrace the advances in TCEM and NAMs if we are to meaningfully bend the time–cost curve for getting new safe and effective therapies to patients.
[1] Dean G. Brown, Heike J. Wobst, Abhijeet Kapoor, Leslie A. Kenna & Noel Southall, “Clinical development times for innovative drugs,” Nature Reviews Drug Discovery 21, (2022): 793–794, https://doi.org/10.1038/d41573-021-00190-9.
[2] Congressional Budget Office (CBO), Research and Development in the Pharmaceutical Industry, (April 2021): 1, https://www.cbo.gov/publication/57126#_idTextAnchor036.
[3] Ibid.
[4] NIH Reporter, Columbia University, Project Number 4UH3EB017103-03, https://reporter.nih.gov/project-details/8768920.
[5] Gail A. Van Norman, “Limitations of Animal Studies for Predicting Toxicity in Clinical Trials: Is it Time to Rethink Our Current Approach?” JACC: Basic to Translational Science 5, no. 4 (2020): 846, 10.1016/j.jacbts.2019.10.008.
[6] Ibid.
[7] CBO, Research and Development, 3, 7.