Research Examines Applications of Model-Informed Drug Development

Regulatory NewsRegulatory News
| 18 January 2019 | By Zachary Brennan 

A new article published in Clinical Pharmacology & Therapeutics digs through case studies, research papers and regulatory documents to highlight some common features of Model-Informed Drug Development (MIDD) applications and future considerations.
The US Food and Drug Administration (FDA) officials from the Office of Clinical Pharmacology explain in the article how MIDD applications can be classified into four categories: dose optimization, supportive evidence for efficacy, clinical trial design and informing policy.

For dose optimization, the authors note challenges in the rare disease area, although a recent survey of orphan drug submissions from 2000 to 2015 indicates an increasing trend in the use of MIDD approaches.

“Two examples of the use of exposure-response analysis to inform dosing are infliximab for the treatment of ulcerative colitis in pediatric patients, and the approval of a lower starting dose of pasireotide for Cushing’s disease,” they write.

On supportive evidence for efficacy, the FDA officials note that their experience with everolimus and canagliflozin/metformin fixed dose combination both “demonstrate the ability of model-based analysis to address complex questions regarding efficacy.”

“There are also cases where the efficacy of excluded subgroups was established based on model-based analyses. When boceprevir was approved to treat HCV patients based on the observed results of the clinical trials, a regimen was also approved for the treatment-experienced subgroup (prior null responders), which was excluded in the phase 3 trial, based on the predicted efficacy from treatment-naïve patients via a novel bridging analysis,” the study says.

The authors further discuss the use of modeling and simulation during the early research phases to inform later phase designs.
And thanks to the sixth iteration of the prescription drug user fee program (PDUFA VI), the FDA officials say that companies should expect to see “a wider range of application of quantitative methods in drug development … along with more consistent acceptance of these approaches by regulatory scientists across therapeutic areas.”
“The inclusion of several MIDD-related provisions in PDUFA VI will allow for 1) increased resources and new mechanisms at the FDA to engage in MIDD activities in product development and review; 2) more opportunity for public stakeholder interaction on key MIDD-related science policy topics; and 3) updated FDA policies and procedures related to MIDD application and regulatory acceptance,” they write.

And although the authors note that several MIDD applications presented in the paper could be viewed as special cases under unique conditions, they also point to the “evolution of modeling and simulation for assessing proarrhythmic risk potential of new drugs” as a counterexample.

As far as a look to the future, the authors highlighted “more mechanistic models, neural network models and real-world data/evidence… and more submissions and experiences are being accumulated to expand the application of model-based analysis to a wider scope.”
The authors added in the conclusion: “The umbrella of MIDD is quite large and, while some model-based analyses have become routine and well accepted, others are still evolving and being evaluated. There are both opportunities and challenges to further incorporating MIDD into rational drug development.”

Meanwhile, details of FDA’s plans for launching a pilot project related to MIDD were recently released and focus on providing advice on how specific, proposed MIDD approaches can be used in a specific drug development program, the agency said. “FDA has committed to accepting two to four meeting requests quarterly each fiscal year. The meetings granted will include an initial and follow-up meeting on the same drug development issues within the span of approximately 120 days.”

Model‐Informed Drug Development: Current U.S. Regulatory Practice and Future Considerations


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