Evaluate and promote the adoption of novel modeling and simulation tools and approaches that can aid in regulatory evaluation of FDA-regulated products
New animal and computer simulation modeling techniques37 are creating innovative opportunities to identify and evaluate sex differences. These techniques can be used to facilitate the study of products at the level of the mechanism of action. These techniques can also be used to predict the toxicity or the safety and efficacy of FDA-regulated products in women including in certain sub-populations (e.g., pregnant women) as well as guide therapy selection and medication dosing for women.
Research in this area should help create predictive models that can take into consideration sex, disease status, and comorbidities, among other critical factors, that may influence the performance of an FDA-regulated product. Research should also help develop models that incorporate sex-specific biomarkers (see next section) that can advance our understanding of unique ways women experience disease manifestation and response to treatment. Better predictive preclinical data from improved models is especially relevant for women as they are more susceptible to some adverse events.38
Research in this area holds the promise of yielding results with major public health benefits. For example, better in silico modeling and simulation of clinical trials (i.e., using computers) hold the promise of strengthening the ability to predict efficacy and adverse events during clinical trials while reducing sample size, making trials more efficient and potentially safer for trial participants. These new techniques can help improve the efficiency of nonclinical and clinical studies, helping to identify promising candidate products earlier in the medical product discovery and development process. This means that safe, new medical products may reach the patients who need them sooner. These new tools can also help identify and characterize contaminants in foods and supplements and predict related outcomes.
3.1 Develop new and leverage existing tools and novel animal, in vitro, and computational models, including those for use in clinical trials to study the toxicity or the safety and efficacy of FDA-regulated products used by women and to study sex differences. Examples include, but are not limited to the following:
- Develop in vivo, in vitro, and computational models to evaluate regulated-product toxicity or the safety and efficacy during pregnancy
- Foster the development of innovative disease models for conditions that affect women, including for rare diseases
- Foster the continued development of models that incorporate human genetics, genomics, molecular signatures, and biomarkers for diseases influenced by sex
- Determine factors relevant to therapy selection and medication dosing considerations in women
- Dietary supplements and toxicity differences
- Identify unique risks that arise for women in the use of specific regulated products to further evaluate the effects of factors that are of concern for female users. For example, products aimed at weight-loss, or mood-alteration, have a large user base of women, and sex or gender-associated risks need to be clearly identified and considered for such products.
- Identify categories of products that would be expected to have differential risk profiles for women vs men; develop a framework as to how the differential risk should be captured and weighed in assessing the toxicity or the safety and effectiveness evaluation of the product. For example, one unique consideration that may arise for female consumers is contact exposure through use of gender-specific topical products such as transdermal estrogen that may result in inadvertent product transfer to others. Because women tend to associate more with children as care-givers, such differential factors should be explicitly identified and evaluated for specific products.
37 FDA is committed to reducing the number of animals used in testing or eliminating their use all together to the extent possible. Computer simulation modeling is one tool that is helping achieve that goal.
38 For example, Torsades de Pointes is a potentially fatal arrhythmia associated with longer QT interval in the ECG. Women are more prone than men to develop torsades de pointes with certain drugs (70% of drug-induced Torsades cases occur in women). See Makkar RR, Fromm BS, Steinman RT, Meissner MD, Lehmann MH. 1993. JAMA. Dec 1;270(21):2590-7; and Ebert SN1, Liu XK, Woosley RL. 1998. Female gender as a risk factor for drug-induced cardiac arrhythmias: evaluation of clinical and experimental evidence. J Womens Health. 1998. Jun;7(5):547-57.