The FDA, based on the success of the MIDD (Model Informed Drug Development) program for discovery that started in 2018, has now launched a similar program for Generics. The “Model-Integrated Evidence” (MIE) Industry Meeting Pilot Program for Generic Drugs, which was launched on October 1st, 2023. If you are thinking about using in silico for your generic drug development program the MIE meeting is a new and essential program to help validate your plan with the FDA and get pre-approvals.
What is MIE pilot program?
The MIE pilot program allows enhanced scientific communications between generic drug developers and FDA on using a broad range of quantitative methods and modeling techniques to address generic drug development issues or questions that are either out of the scope of or cannot be sufficiently addressed by the existing pre-ANDA and ANDA scientific meetings.
Specifically, the pilot MIE meeting(s) will focus on discussing scientific and technical topics of using MIE strategies for BE establishment (e.g., feasibility, details in model building, and/or model verification and validation data) while pre-ANDA meetings will be focused on more general scientific and regulatory issue(s).
What are the eligibility criteria for the MIE Pilot Program?
- Innovative MIE-Focused Approaches: Eligible if they address complex issues for BE establishment not covered by existing pre-ANDA and ANDA scientific meetings, such as validating a computational fluid dynamics (CFD) model for predicting regional deposition of inhaled aerosols from various orally inhaled drug products (OIDPs).
- Non-Complex Products with Complex Modeling: Eligible for products with complex modeling supporting BCS-based biowaivers and other BE study waivers beyond current recommendations.
- Novel Data Analytics Tools: Eligible for novel data analytics tools, including advancements in modeling methodology or new applications, such as equivalence analysis of complex particle size distribution, new quantitative approaches for sameness assessment, and the application of novel data analytics approaches like machine learning methodology for equivalence assessment.
Why should I do it?
- FDA Acceptance: Modeling and Simulation is being widely used in drug development programs and is being accepted by the FDA as evidence for regulatory decision making. If you are thinking about using in silico Modeling and Simulation approaches for your generic drug development program, and looking to supplement your FDA filings with in silico data, then MIE pilot meeting is new and essential program to help validate your plan with the FDA and get pre-approvals.
- Efficiency Gains: MIE principles have proven instrumental in expediting drug development timelines, with estimated time savings ranging from a few months to over two years. The companies surveyed reported significant reductions in development costs, reaching up to $50 million. Mechanisms for time and cost savings included accelerated timelines, reduced trial sizes, and obviating the need for certain clinical trials.
- Alignment: Alignment emerged as a crucial benefit, both with the FDA and internally within pharmaceutical companies. Focusing on specific topics during the paired meetings allowed for targeted discussions, resulting in agreement on development strategies. The program’s iterative nature provided a unique opportunity for companies to align not only with regulatory expectations but also internally across various functions.
- Learning and Clarity: Participants acknowledged the invaluable insights gained from FDA colleagues during the meetings. Clarity on regulatory expectations, feedback on methodologies, and discussions on technical feasibility have positively impacted development programs. These interactions have not only clarified aspects of individual programs but also contributed to building consensus within the pharmaceutical industry and shaping future regulatory policies.
What are the potential topics I can discuss with the FDA at a MIE Meeting?
The MIE Program as discussed can help validate and pre-approve modeling and simulation approaches for various generic drug use cases. Here is an extensive but not exhaustive list of some possibilities.
Meeting topics related to the Division of Quantitative Methods and Modeling (DQMM) plays a crucial role through its four quantitative disciplines: oral PBPK, non-oral PBPK, QCP (Quantitative Clinical Pharmacology), and data analytics. These disciplines collectively contribute to a wide array of topics that are pertinent to the industry. The topics, not exhaustive but carefully curated from previous industry interactions with DQMM, encompass various stages of drug development, including pre-ANDA meetings, controlled correspondence (CCs), ANDA assessment, and post-submission meetings.
Table 1 – Oral PBPK modeling –
| Category | Potential discussion topics |
| Risk assessment of deviation of dissolution profiles on BE | Using PBPK absorption model to evaluate the impact of non-comparable dissolution profiles of lower strength on BE and support biowaiver for oral products including immediate release (IR) and extended release (ER) products. |
| Risk assessment of the impact of Particle Size Distribution (PSD) on BE | Using PBPK modeling to evaluate the risk of impact of Particle Size Distribution (PSD) on BE and support setting a clinically relevant PSD specification for a generic product |
| Risk assessment of non-comparable in vitro alcohol dose dumping studies | PBPK modeling to evaluate the impact of in vitro alcohol dose dumping on BE study |
| Identify bio-predictive dissolution and support BE evaluation | PBPK absorption modeling to help identify bio-predictive dissolution and support BE evaluation for a gastrointestinal (GI) locally acting product |
| Support waiver of fed BE study for high-risk product | Using PBPK modeling to evaluate the impact of food on BE for high-risk products |
| Support waiver of BE study in subjects with gastric pH change | Using PBPK modeling to evaluate the impact of gastric pH on BE |
| Support BCS based biowaiver | PBPK modeling to evaluate the impact of excipients on bioequivalence of BCS class III drug products |
| Justify BE study design | PBPK modeling to evaluate the impact of including single-sex subjects on BE PBPK modeling to evaluate the sensitivity of BE analyte (parent vs. metabolite) |
Table 2 – Non-oral PBPK modeling –
| Category | Potential discussion topics |
| Model Validation for OIDPs | Validation of regional deposition models for orally inhaled drug products (OIDPs) |
| Describe drug delivery to the site of action for OIDPs | Application of PBPK modeling to understand relationships of in vitro and in vivo metrics with drug delivery to the site of action for OIDPs |
| Model validation for topical dermatological drug products | Validation of in vivo dermal PBPK models and in silico IVPT models using percutaneous pharmacokinetic (IVPT, dermal microdialysis and dOFM) or systemic PK data: considerations for RLD and T products based on formulation composition differences |
| Model platform development and validation | Platform validation for locally acting drug products: considerations for in vivo PBPK models for locally acting drug products or in silico IVPT models for topical dermatological drug products supporting platform validation |
| In silico IVPT model | Methodology on the development and validation of the in silico IVPT model for topical dermatological drug products with API of low skin permeation or products with IVPT study challenges Application of the validated in silico IVPT model to inform in vivo dermal models through validated IVIVEs for topical dermatological drug products |
| Models on drug release for drug products with unique formulation characteristics | Development and validation of drug release models for drug products with unique formulation characteristics (topical dermatological drug products: microsphere formulations, PLGA-based LAIs, ophthalmic (biodegradable) inserts, etc.) that may require innovative approaches |
| Model-based interspecies scaling | Interspecies model extrapolations to humans for ophthalmic and LAI drug products: usage of PBPK modeling approach |
| LAI PBPK model | Development of LAI PBPK model accounting formulation attributes, local physiology and their interplay to describe the in vivo release and subsequent absorption of API from the injection site |
Table 3 – QCP (Quantitative Clinical Pharmacology) and VBE (Model-Based Drug Development & BE Assessment)
| Category | Potential discussion topics | |
| Alternative Study Designs … | ||
| with shortened overall duration (e.g., for LAIs, for studies in sensitive patient populations) | In silico continuation – population PK (PopPK) to continue in silico dosing of a non-steady state study and evaluate BE at steady state Carryover adjustment – PopPK-based adjustment for carryover effect in patient single-dose crossover studies with no washout period PopPK-based support of AUC truncation PopPK-based support of truncated study design with alternative evaluation criteria (e.g., narrowed BE limits) PopPK-based support for alternative study designs such as switch-over study designs and repeated designs | |
| with decreased number of subjects (e.g., for orphan drugs, for studies in sensitive patient populations) | Along with shortened study designs (i.e., non-steady state studies), additional incorporation of replicate reference sequences for use of reference-scaling Sparse or reduced sampling optimized design strategies supported by model-based BE evaluation | |
| Practical study considerations & BE assessment challenges | Assessment of steady state attainment through popPK modeling Accounting for missed samples (in PK or PD) through popPK modeling; data imputation approaches Model-based adaptive design Justification in deviations in PK profiles (e.g., Tmax, Tlag) through popPK and PK/PD modeling Model-based Emax determination in dose-scale PD studies | |
| PK/BE bridging | Bridging to alternative product when reference standard is discontinued | |
Table 4 – Data analytics –
| Category | Potential discussion topics |
| Complex comparative profile analysis | Equivalence analysis of complex particle size distribution; Comparative analysis of LC/MS profile |
| Complex substance analysis | Novel quantitative modeling and methods for complex substance analysis |
| Novel data analytic tool | Utilization of artificial intelligence (such as machine learning) to support data analysis and/or model building in the submission |
How do I apply for the MIE Program and what are the stages of the process?
At InSilicoMinds, we pride ourselves on seamlessly facilitating crucial interactions between pharmaceutical companies and regulatory bodies, ensuring a streamlined process for our clients. In our commitment to advancing healthcare solutions, we specialize in arranging engagements such as the Model-Integrated Evidence (MIE) Pilot Program meetings with the U.S. Food and Drug Administration (FDA).
Our expertise lies in navigating the complex stages of the MIE Pilot Program, including meeting request submission, preparation, conduct, and post-meeting communications. We understand that successful communication with the FDA is pivotal for bringing cutting-edge pharmaceutical products to market. With InSilicoMinds, you gain a strategic partner dedicated to navigating the regulatory landscape on your behalf.
The MIE Pilot Program Process consists of three stages:
Stage 1 – Meeting Request/Package Submission:
- Applicable to both complex and non-complex products.
- Focus on proposed MIE bioequivalence approach.
- Include specific technical questions and the complete meeting package.
- Full dataset may not be required initially but may be requested if the meeting is granted.
- Do not submit multiple requests or controlled correspondences (CCs) for the same product simultaneously.
Stage 2 – Meeting Preparation and Conduct:
- Occurs if the meeting request is granted.
- Includes up to two video-conference meetings between the applicant and FDA.
- Optional Orientation Meeting, requested at FDA’s discretion, approximately 30 days from the grant date.
- Preliminary responses sent before the external meeting date.
- Final External Meeting scheduled within 120 days (or 150 days if an optional orientation meeting was held) from the grant date.
Stage 3 – Post-Meeting FDA Communication:
- Applicants may submit a meeting summary within 7 days of the final external meeting.
- The FDA aims to issue meeting minutes within 30 days of the meeting date, which serve as the official record.
Additional Points:
- MIE meeting requests do not guarantee a meeting; FDA evaluates and decides within 14 days.
- If a meeting is denied, the applicant can explore other communication pathways aligning with FDA’s normal procedures.
- The meeting package includes a cover letter, general information, meeting information, and details on MIE utilization and approaches.
- The complete meeting package is submitted via email, and a confirmation of receipt is sent by FDA – MIE@fda.hhs.gov
- The meeting timeline for Stage 1 is 14 days, Stage 2 is 120-150 days, and Stage 3 is 30 days.
- The final external meeting follows the applicant’s agenda, as determined after preliminary comments.
Conclusion:
As we have observed from the recent webinar, the MIE pilot program offers an invaluable opportunity for generic drug developers to engage in enhanced scientific communications with the FDA. By focusing on the application of a wide range of quantitative methods and modeling techniques, the program addresses issues beyond the scope of existing pre-ANDA and ANDA scientific meetings.
The benefits of participating in the MIE meeting pilot program are substantial. The FDA’s acceptance of modeling and simulation as evidence for regulatory decision-making is a significant milestone, allowing companies to supplement their FDA filings with in silico data. Beyond regulatory acceptance, companies can achieve efficiency gains, with estimated time savings and reductions in development costs, reaching up to $50 million.
Moreover, the learning and clarity gained from interactions with FDA colleagues during the meetings are invaluable. These insights contribute to a better understanding of regulatory expectations, methodologies, and technical feasibility, positively impacting the development programs and fostering consensus within the pharmaceutical industry.
InSilicoMinds, stands as a strategic partner dedicated to navigating the regulatory landscape on behalf of our clients, providing support at every stage of the MIE Pilot Program process. With a focus on meeting request submission, preparation, conduct, and post-meeting communications, we ensure our clients have the best chance of success in their engagement with the FDA, ultimately advancing healthcare solutions and bringing cutting-edge pharmaceutical products to market.
