Evidence map›Paper›PMID 35348922›Full record

ArticleThe AAPS journal2022

An IQ Consortium Perspective on Connecting Dissolution Methods to In Vivo Performance: Analysis of an Industrial Database and Case Studies to Propose a Workflow.

Aktham Aburub, Yuan Chen, John Chung, Ping Gao, David Good, Simone Hansmann, Michael Hawley, Tycho Heimbach, Martin Hingle, Filippos Kesisoglou and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
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

13 authors.

Aktham AburubEli Lilly and Company, Indianapolis, Indiana, USA.
Yuan ChenGenentech, San Francisco, California, USA.
John ChungAmgen Inc., Thousand Oaks, California, USA.
Ping GaoAbbVie Inc., North Chicago, Illinois, USA.
David GoodBristol-Myers Squibb Company, New Brunswick, New Jersey, USA.
Simone HansmannThe healthcare business of Merck KGaA, Darmstadt, Germany.
Michael HawleyBoehringer Ingelheim, Ridgefield, Connecticut, USA. michael_x.hawley@boehringer-ingelheim.com.
Tycho HeimbachPharmaceutical Sciences, Merck & Co., Inc, Rahway, New Jersey, USA.
Martin HingleMedicinal Science and Technology, GlaxoSmithKline R&D, Park Road, Hertfordshire, UK.
Filippos KesisoglouPharmaceutical Sciences, Merck & Co., Inc., Kenilworth, New Jersey, USA.
Rong LiPfizer Inc., Groton, Connecticut, USA.
John RoseEli Lilly and Company, Indianapolis, Indiana, USA.
Christophe TisaertJohnson & Johnson, New Brunswick, New Jersey, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of bioperformance to inform formulation selection and development decisions is an important aspect of drug development. There is high demand in the pharmaceutical industry to develop an efficient and streamlined approach for better understanding and predicting drug product performance to support acceleration of clinical timelines. This manuscript presents an effort from the IQ Formulation Bioperformance Prediction Working Group composed of members from 12 pharmaceutical companies under the IQ Consortium to develop a database around the topic of formulation bioperformance prediction and report findings from the database analysis. Six case studies described in the manuscript demonstrate how bioperformance models were used to predict in vivo performance and to provide guidance addressing questions encountered during oral solid dosage form development. The case studies also described findings of a correlation between in vitro dissolution and in vivo performance and how dissolution data can be incorporated into physiologically based biopharmaceutical modeling. Finally, a workflow for how in vitro dissolution data can be utilized to predict clinical bioperformance of oral solid dosage forms is proposed.

Indexed as

Drug DevelopmentModels, BiologicalAdministration, OralIntestinal AbsorptionSolubilityWorkflowabsorptiondissolutionmodeling and simulationparticle sizePBBMpermeabilitysolubility

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.