Preclinical testing serves a fundamental role in characterizing the potential risks associated with new FDA-regulated products. But serious and sometimes rare and unexpected adverse events may be observed in clinical trials or post-approval, suggesting that critical gaps exist in our understanding of the relationship between patient response and preclinical toxicology findings.
For example, non-clinical safety assessment is often conducted in normal healthy test systems and tends to be exposure-based; it does not attempt to evaluate the possible risk of rare or idiosyncratic responses that may arise from potential interactions with the presence or progression of disease or the genetic background or other exposures of patients and consumers.
Also, in some cases, the true predictive accuracy of many toxicology models and safety assays remains uncertain and in need of more rigorous validation against actual human and animal adverse event data to define their reliability and possible limitations.
For tobacco products, a deeper understanding of the negative effects of tobacco constituents and how best to measure and, wherever possible, reduce those effects is needed to assess public health impact.
Finally, introducing new measurement technologies and increasing knowledge about toxicity mechanisms and pathways offer important opportunities for advanced computational analyses that can promote the effective translation of non-clinical findings to the clinical setting.
FDA can close these gaps and improve preclinical safety predictions by further investing in three particular areas of regulatory science: evaluating and developing models and assays that better predict patient response; identifying and evaluating more reliable biomarkers for monitoring toxicities, side effects, and abnormalities; and using computational tools to integrate and draw conclusions from a wide range of preclinical safety data types and sources.
FDA will seek to improve the prediction of product safety and efficacy based on preclinical data by conducting internal and collaborative research to address the following needs:
- Develop better models of human adverse response:
- Evaluate and promote the use of cell and tissue based assays that more accurately represent human susceptibility to adverse reactions;
- Modernize the development and use of animal models that consider the potential influence of disease progression and disease co-morbidities on the emergence of adverse events;
- Promote a better understanding of toxicity mechanisms by evaluating safety assessment data at multiple levels of biological organization, including genes, proteins, pathways, and cell/organ function;
- Assess and characterize molecular targets and host genetic factors that may be associated with rare and unexpected adverse events (“off-target” drug effects); and
- Initiate in vitro and in vivo studies to identify potential markers of harm associated with exposure to tobacco constituents.
- Identify and evaluate biomarkers and endpoints that can be used in non-clinical and clinical evaluations:
- Evaluate the accuracy (specificity and sensitivity) with which animal models and cell-based assays correctly predict potential human risk;
- Assess concordance between animal and human markers of toxicity and determine how the performance of these markers and their interpretation may vary across different organ systems and human populations; and
- Evaluate quantitative imaging (e.g. positron emission tomography, magnetic resonance imaging, computed tomography) and other advanced approaches (e.g. metabolomics) for identifying new biomarkers and predictors of efficacy and safety.
- Use and develop computational methods and in silico modeling:
- Improve the use of chemical Structure-Activity Relationship (SAR) models in the prediction of human risk and integrate this analysis into the review process;
- Develop and implement approaches to link chemical structures and substructures to a wide range of information about product safety, disease targets, and toxicity mechanisms;
- Develop clinical trial simulation models that can reveal interactions between drug or device effects, patient characteristics, and disease variables influencing outcomes
- Develop computer models of cells, organs, and systems to better predict product safety and efficacy;
- Implement computer models that integrate pharmacokinetic, pharmacodynamic, materials science, or mechanistic safety data to predict clinical risk-benefit and confirm post-marketing safety in different patient populations; and
- Develop and apply data mining, knowledge building, and data visualization tools to inform computer model development, clinical risk prediction, and regulatory decision-making.
New Models to Assess Safety of Gene Therapy
There are currently numerous clinical trials using a promising new class of cancer therapies based on adenovirus—a variation of a common cold virus that can be engineered to deliver cancer-killing gene therapies. However, rapid clearance of adenovirus by the liver prevents the virus from finding the target cancer cells and, in some cases, may cause liver toxicity. FDA scientists have developed animal models to study how the liver clears adenovirus from circulation and how adenovirus trigger toxic reactions. As a result, they have been able to identify methods to block receptors that the liver uses to clear adenovirus vectors from circulation. They have also identified adenovirus-induced mediators that could potentially be blocked to improve safety. For example, adenovirus injections in rats and mice rapidly induce toxic mediator that can cause lethal shock. Scientists can block this mediator with a drug, completely protecting the animals from shock.
Public Health Impact:
By addressing these needs, FDA will be better able to identify and accurately predict and reduce the magnitude and likelihood of risks associated with products. This, in turn, will help both speed and reduce costs in achieving the delivery of safe and effective new products to market, leading to improved health outcomes and reduced patient risk. By continuing to explore and integrate new tools and approaches in the evaluation of product safety, FDA will be better able to estimate dose ranges, help promote more informed device designs for safe use in clinical trials, and develop and use more sensitive and reliable ways to identify and confirm safety issues at earlier times during the medical product development process. FDA Centers will also be better able to anticipate the risk and nature of product-related adverse events and to understand the mechanisms by which these events occur in specific individuals or subpopulations. Modernizing toxicology and continually improving the ability of non-clinical tests, models, and measurements to predict product safety issues will increase the likelihood that toxicity risks will be identified earlier in product development, assuring patient safety, and mitigating the need to withdraw previously approved products.