Evidence map›Paper›PMID 42198230›Full record

ReviewPharmaceutics2026

Model-Integrated Bioequivalence (MIBE) in Generic Drug Research: Can We Ease the Bioequivalence Burden?

Sivacharan Kollipara, Rajkumar Boddu, Chandra Teja Uppuluri, Anuj Kumar Saini

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sivacharan KolliparaBiopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500090, Telangana, India.ORCID 0000-0002-7332-9021
Rajkumar BodduBiopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500090, Telangana, India.ORCID 0000-0002-8666-3643
Chandra Teja UppuluriBiopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500090, Telangana, India.ORCID 0000-0002-8563-5974
Anuj Kumar SainiBiopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500090, Telangana, India.ORCID 0000-0001-7131-4267

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bioequivalence (BE) studies are essential to file an abbreviated new drug application (ANDA) against an innovator drug product. Conventional BE studies can be complex, time-consuming, and operationally challenging, particularly for products with long half-life drugs, high variability, or formulation complexity. Advances in quantitative modeling and simulation have expanded the role of model-generated information in generic drug development from a supportive role toward providing critical regulatory evidence. Model-Integrated Bioequivalence (MIBE) represents a focused application of this paradigm in which mechanistic or empirical models are used to directly support BE determination. While physiologically based pharmacokinetic (PBPK) and physiologically based biopharmaceutics modeling (PBBM) approaches have been widely discussed in the literature, increasing attention is being directed toward population pharmacokinetic (POP-PK) modeling for MIBE implementation, particularly when mechanistic assumptions are uncertain or extensive in vitro characterization is impractical. This review provides a contemporary overview of MIBE in generic drug development, with a specific emphasis on POP-PK-based approaches. Key quantitative modeling frameworks are discussed along with evolving regulatory perspectives that support the integration of model-based evidence for BE assessment. We illustrate six diverse hypothetical case examples covering different formulations, a variety of BE scenarios and using MIBE to answer specific regulatory questions on BE. Collectively, this manuscript addresses an important topic of MIBE for complex and non-complex generic formulations and may provoke thinking among the generic companies to use such approaches in the regulatory context to enable faster and timely approval to bring the necessary medicines to the market at a rapid pace.

Indexed as

alternative BEbioequivalencegeneric product developmentMIBEPBBMPBPKregulatory

Identifiers

PMID42198230
PMCPMC13210687

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.