In May 2022, the Center for Drug Evaluation and Research (CDER) of the U.S. Food and Drug Administration (FDA) launched its Accelerating Rare disease Cures (ARC) Program1 with the vision of speeding and increasing the development of effective and safe treatment options addressing the unmet needs of patients with rare diseases.
This is a very timely initiative to coordinate all CDER rare disease activities and to bring together multiple stakeholders. The initial success of this program was demonstrated through two workshops2,3 dedicated to designing clinical trials for rare diseases and developing surrogate endpoints, biomarkers, and more. Both workshops emphasized the need for innovative approaches, patient engagement, and collaboration.
Innovative approaches, collaboration, and engagement are critical for any drug’s development. However, in the case of developing treatments for the estimated 7,000 rare diseases, the need for innovation is a “must have,” not a “nice to have.”
In the last decade, we have made significant progress in understanding the natural history and etiology of many rare diseases. But there is still hesitation among researchers, sponsors, and patients when it comes to applying modeling and simulation to the area of rare diseases. At Certara, we believe there is a need for significant educational efforts to modernize drug development programs. Unfortunately, the current paradigm of drug development for rare disease still follows the traditional “linear” approach, as presented in Figure 1 with the engagement of patients, subject matter experts (SME), and the FDA at pre-defined stages of product development, and use of modeling and simulation on “as needed” basis, rather than incorporating it into the program from the beginning.
Figure 1: Traditional “linear’ approach to drug development
With the current state of knowledge and the limited number of potential rare disease trial participants, the paradigm should shift from a “linear” to a “cycle” approach, in which engagement with patients, SMEs, and FDA are at the core of a drug’s development, and modeling and simulation are integrated into development, as presented in Figure 2.
図2：Modern “cycle” approach to rare disease drug development
The following case study demonstrates the advantages of this modern approach through application of modeling to optimize trial design for a rare disease.
Modeling and simulation was used to generate evidence in support of regulatory qualification of total kidney volume (TKV) as a prognostic biomarker for use in clinical trials for autosomal dominant polycystic kidney disease (ADPKD), which is a rare hereditary kidney disease.4
The modeling and simulation tool was developed by Certara in collaboration with the Polycystic Kidney Disease Outcomes Consortium (PKDOC)5 by linking longitudinal TKV to the probability of a 30% decline of estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD). Baseline characteristics of subjects with ADPKD included in the joint model analysis are presented in Table 1.
Data utilized for analysis came from registries as opposed to clinical trials, and patients were seen on an irregular basis. The populations used in modeling the probability of a 30% decline of eGFR consisted of 1140 subjects with mean baseline TKV, age, and eGFR of 1141 ml, 33.2 years, and 84.3 ml/min per 1.73 m2, respectively. For ESRD, a total of 316 patients were excluded because of missing baseline eGFR or a missing date of ESRD. For the ESRD model, a total of 866 patients with at least 2 TKV measurements separated by at least 6 months were included in the analysis, 147 of whom developed ESRD (17.0%).
Table 1: Trial enrichment example—tabulation of predicted probabilities of observing a 30% decline of eGFR as a function of baseline TKV, eGFR, or age.
Adequacies of event models, linking individual subject level TKV data to a 30% decline of eGFR and ESRD endpoints over follow-up time, are presented in Figure 3. Time to a 30% decline of eGFR and ESRD endpoints were well-fitted with the joint model as demonstrated by the model-predicted value (red line) relative to observed probabilities (black lines) and 95% confidence intervals.
図3：Model-predicted versus observed probabilities for avoiding a 30% decline of eGFR and ESRD over time. eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease.
Overall, the qualification of TKV as an imaging biomarker for tracking and predicting the natural history of ADPKD represents a significant, innovative step forward to establishing the commitment of health authorities, clinicians, and patients to address the unmet needs for this debilitating condition, thereby encouraging researchers and the pharmaceutical industry to develop promising new therapies for these patients.4 This model development is one successful example of innovation. The information on this model development is published4 and additional educational resources can be provided by Certara upon request.
In conclusion, effective drug development for rare diseases can happen only through innovation, collaboration, and education. The FDA’s ARC program is a step in the right direction and will help to accelerate rare disease drug development.
To learn more about how Certara supports drug development for rare diseases, visit our resource center:
- FDA CDER’s ARC Program. Last accessed 20-June-22: https://www.fda.gov/about-fda/center-drug-evaluation-and-research-cder/cders-arc-program
- FDA CDER & NIH NCATS Regulatory Fitness in Rare Disease Clinical Trials Workshop- May 16-17, 2022. Last accessed 20-June-22: https://www.fda.gov/drugs/news-events-human-drugs/fda-cder-nih-ncats-regulatory-fitness-rare-disease-clinical-trials-workshop-05162022
- FDA and Duke-Margolis Public Workshop: Translational Science in Drug Development: Surrogate Endpoints, Biomarkers, and More External Link Disclaimer May 24-25, 2022. Last accessed 20-June-22: https://healthpolicy.duke.edu/events/translational-science-drug-development-surrogate-endpoints-biomarkers-and-more
- R. Perrone, M.-S. Mouksassi, K. Romero, et al. A Drug Development Tool for Trial Enrichment in Patients with Autosomal Dominant Polycystic Kidney Disease. Kidney Int Rep. 2017 May; 2(3): 451～460. Published online 2017 Feb 21. Last accessed 23-June-22: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678607
- Critical Path Institute, The Polycystic Kidney Disease (PKD) Outcomes Consortium. Last accessed 23-June-22: https://c-path.org/programs/pkd/