Literature DB >> 32719954

Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products.

Arzu Selen1, Anette Müllertz2, Filippos Kesisoglou3, Rodney J Y Ho4, Jack A Cook5, Paul A Dickinson6, Talia Flanagan7.   

Abstract

Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.

Entities:  

Keywords:  biopharmaceutics; blueprint meetings; decision-making for the system; integrated risk assessment; systems thinking

Mesh:

Year:  2020        PMID: 32719954     DOI: 10.1208/s12248-020-00470-z

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  37 in total

1.  Model-Based Analysis of Biopharmaceutic Experiments To Improve Mechanistic Oral Absorption Modeling: An Integrated in Vitro in Vivo Extrapolation Perspective Using Ketoconazole as a Model Drug.

Authors:  Shriram M Pathak; Aaron Ruff; Edmund S Kostewicz; Nikunjkumar Patel; David B Turner; Masoud Jamei
Journal:  Mol Pharm       Date:  2017-08-25       Impact factor: 4.939

Review 2.  The use of modeling tools to drive efficient oral product design.

Authors:  Neil R Mathias; John Crison
Journal:  AAPS J       Date:  2012-05-30       Impact factor: 4.009

3.  The developability classification system: application of biopharmaceutics concepts to formulation development.

Authors:  James M Butler; Jennifer B Dressman
Journal:  J Pharm Sci       Date:  2010-12       Impact factor: 3.534

Review 4.  Why and how have drug discovery strategies in pharma changed? What are the new mindsets?

Authors:  Serge Mignani; Scot Huber; Helena Tomás; João Rodrigues; Jean-Pierre Majoral
Journal:  Drug Discov Today       Date:  2015-09-14       Impact factor: 7.851

5.  Physiologically Based Absorption Modeling to Impact Biopharmaceutics and Formulation Strategies in Drug Development-Industry Case Studies.

Authors:  Filippos Kesisoglou; John Chung; Judith van Asperen; Tycho Heimbach
Journal:  J Pharm Sci       Date:  2016-01-23       Impact factor: 3.534

Review 6.  Paving the critical path: how can clinical pharmacology help achieve the vision?

Authors:  L J Lesko
Journal:  Clin Pharmacol Ther       Date:  2007-02       Impact factor: 6.875

7.  Health systems, systems thinking and innovation.

Authors:  Rifat Atun
Journal:  Health Policy Plan       Date:  2012-10       Impact factor: 3.344

Review 8.  Learning versus confirming in clinical drug development.

Authors:  L B Sheiner
Journal:  Clin Pharmacol Ther       Date:  1997-03       Impact factor: 6.875

9.  A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability.

Authors:  G L Amidon; H Lennernäs; V P Shah; J R Crison
Journal:  Pharm Res       Date:  1995-03       Impact factor: 4.200

Review 10.  Moving from basic toward systems pharmacodynamic models.

Authors:  William J Jusko
Journal:  J Pharm Sci       Date:  2013-05-16       Impact factor: 3.534

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  1 in total

1.  Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series.

Authors:  Mark McAllister; Talia Flanagan; Susan Cole; Andreas Abend; Evangelos Kotzagiorgis; Jobst Limberg; Heather Mead; Victor Mangas-Sanjuan; Paul A Dickinson; Andrea Moir; Xavier Pepin; Diansong Zhou; Christophe Tistaert; Aristides Dokoumetzidis; Om Anand; Maxime Le Merdy; David B Turner; Brendan T Griffin; Adam Darwich; Jennifer Dressman; Claire Mackie
Journal:  Pharmaceutics       Date:  2022-05-07       Impact factor: 6.525

  1 in total

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