The traditional focus of preclinical studies has always been on safety.
And for good reason.
Many global medical regulatory bodies can trace their origins to specific drug-related catastrophes. The core focus on preventing harm to humans extends to first-in-human trials of new drugs. Regulators often demand overwhelming evidence of the safety of a candidate drug before human testing is authorized.
The FDA is quite clear on this, per the Code of Federal Regulations defining Investigational New Drug (IND) Applications:
“FDA’s primary objectives in reviewing an IND are, in all phases of the investigation, to assure the safety and rights of subjects”
While this focus makes sense, lack of scrutinized efficacy data may drive a problem with its own harms: the extremely high failure rate of drugs in clinical trials. Overall, approximately 90% of clinical trial drugs fail to make it to market. While unmanageable toxicity contributes 30% of that total, lack of efficacy can contribute to as much as 50%.
As newer, complex technologies become available to better predict efficacy prior to human testing, a question becomes increasingly important, “should regulators require a demonstration of human-relevant efficacy prior to authorizing human trials?”
Efficacy Is Important but Difficult to Measure in Animals
To be clear, drug developers do robustly test efficacy of candidate drugs. This is a critical aspect of their long-term planning and decision-making around new drugs. They use a wide array of computational, in vitro, and animal disease models to evaluate potential efficacy. However, the FDA has been quite clear on the utility of those animal disease models. Even when discussing the need for efficacy models (to better predict toxicity at doses required to see biological activity) the FDA says, “Potential limitations of these preclinical animal models can exist. Examples of these limitations include: […] Limited fidelity in modeling human pathophysiology of the disease/injury of interest.”
You’ve probably heard the jokes. “How many more times are we going to have to read an article about how they found a new cure for cancer that only works on rats?” And it extends far beyond cancer. Human neurodegenerative diseases are particularly challenging. Alzheimer’s Disease has had a clinical failure rate above 99%.
Efficacy Failures Do Harm Humans
The prioritization of safety over efficacy in IND speaks to regulators’ risk-based approaches that favor prevention of harm in patients. However, even if a drug does not directly harm a clinical trial participant, lack of efficacy in Phase II and Phase III clinical trials does cause serious harm to individual patients and public health for multiple reasons:
- Despite clear communication to the contrary, many clinical trial patients, who are seriously ill and seeking a “Hail Mary”, have high expectations that the clinical trials will cure them.
- The failure of a clinical drug to treat a disease is a devastating outcome for patients in the trial.
- Drugs are in clinical trials because there is a medical need for a treatment. With finite clinical trial participants and finite resources, drug development is often constrained by capital and time. Efficacy failures also typically appear after Phase II or Phase III (the most money and time intensive phases) are complete.
- Ineffective drugs inadvertently taking priority and resources over more effective drugs harms public health.
- Even with extraordinarily robust safety testing, the risk to clinical trial patients is never zero. If a validated, human-relevant efficacy model indicated an extremely low probability of benefit, its risk-benefit ratio would be considered unacceptably high. The trial would not be authorized, and the clinical trial participants would not be exposed to unnecessary risk.
- It is statistically likely that trial participants have been harmed by candidate drugs that were also ineffective.
Advanced Human-Relevant Disease Models Are Emerging
New Approach Methodologies (NAMs) represent a revolution of biomedical development. The deployment of complex cell-based, computational, and other methods with sophisticated, human-relevant outputs has extraordinary potential to produce better medicines and has received significant regulatory attention over the past year. NAMs technologies are broad and have the potential to answer a wide array of questions relevant to drug development, particularly efficacy. Regulatory qualifications programs, such as the FDA’s ISTAND Program, are providing a clear path for NAMs data to take a central role in preclinical decision-making. However, to date, preclinical NAMs accepted into the ISTAND program overwhelmingly favor safety endpoints, with none yet in the program to assess efficacy.
A Call for Change
There are still major limitations to the adoption of NAMs to demonstrate efficacy in preclinical testing. These include that most diseases do not yet have validated NAMs models, no NAMs disease model has received regulatory qualification, and a legal framework for that requirement does not exist in most jurisdictions. However, validated NAMs models and service providers do exist for many of the diseases with the highest failure rates. Therefore, I believe it is time for a change:
Where validated models exist, regulators should begin actively qualifying efficacy-focused NAMs and make their use standard for therapies targeting diseases with the highest clinical failure rates.
Choose InnovApproach Consulting
If your team is developing a NAM and wants to ensure it is validated, qualified, and positioned for regulatory acceptance, contact InnovApproach Consulting. We’ll help you navigate the complex NAMs environment to secure regulatory recognition and long-term adoption.
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