Dataset Information

A modelling framework for improved design and decision-making in drug development.

ABSTRACT: The development of a new drug is an extremely high-risk enterprise. The attrition rates of development projects and the average costs for each launched product are daunting, and the completion of a development program requires a very long time horizon. These facts imply that there are huge potential gains, should one be able to improve efficiency and enhance decision-making capabilities. In this paper, we argue that substantial gains can be achieved by adapting a holistic view of drug development. Historically, too much planning, design and decision-making in the pharmaceutical development has been based on locally optimising separate parts of the development program, and too often important sources of uncertainty are ignored. We propose instead a model-based approach built on two essential pillars; (1) an integrated holistic view of the development program, including post-launch marketing and sales, with all parts evaluated simultaneously; (2) an explicit appreciation of all relevant sources of uncertainty. Computer simulations are utilised to evaluate the properties of the program options at hand, and to provide valuable quantitative decision support. Applications of this modelling approach have proven to add large value to development projects in terms of better program options being generated and more value-adding decisions taken.

SUBMITTER: Wiklund SJ

PROVIDER: S-EPMC6713335 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A modelling framework for improved design and decision-making in drug development.

Wiklund Stig Johan SJ

PloS one 20190828 8

The development of a new drug is an extremely high-risk enterprise. The attrition rates of development projects and the average costs for each launched product are daunting, and the completion of a development program requires a very long time horizon. These facts imply that there are huge potential gains, should one be able to improve efficiency and enhance decision-making capabilities. In this paper, we argue that substantial gains can be achieved by adapting a holistic view of drug developmen ...[more]

PMID: 31461440

Similar Datasets

Project description:Background:Decision-making in public health and health policy is complex and requires careful deliberation of many and sometimes conflicting normative and technical criteria. Several approaches and tools, such as multi-criteria decision analysis, health technology assessments and evidence-to-decision (EtD) frameworks, have been proposed to guide decision-makers in selecting the criteria most relevant and appropriate for a transparent decision-making process. This study forms part of the development of the WHO-INTEGRATE EtD framework, a framework rooted in global health norms and values as reflected in key documents of the World Health Organization and the United Nations system. The objective of this study was to provide a comprehensive overview of criteria used in or proposed for real-world decision-making processes, including guideline development, health technology assessment, resource allocation and others. Methods:We conducted an overview of systematic reviews through a combination of systematic literature searches and extensive reference searches. Systematic reviews reporting criteria used for real-world health decision-making by governmental or non-governmental organization on a supranational, national, or programme level were included and their quality assessed through a bespoke critical appraisal tool. The criteria reported in the reviews were extracted, de-duplicated and sorted into first-level (i.e. criteria), second-level (i.e. sub-criteria) and third-level (i.e. decision aspects) categories. First-level categories were developed a priori using a normative approach; second- and third-level categories were developed inductively. Results:We included 36 systematic reviews providing criteria, of which one met all and another eleven met at least five of the items of our critical appraisal tool. The criteria were subsumed into 8 criteria, 45 sub-criteria and 200 decision aspects. The first-level of the category system comprised the following seven substantive criteria: "Health-related balance of benefits and harms"; "Human and individual rights"; "Acceptability considerations"; "Societal considerations"; "Considerations of equity, equality and fairness"; "Cost and financial considerations"; and "Feasibility and health system considerations". In addition, we identified an eight criterion "Evidence". Conclusion:This overview of systematic reviews provides a comprehensive overview of criteria used or suggested for real-world health decision-making. It also discusses key challenges in the selection of the most appropriate criteria and in seeking to implement a fair decision-making process.

Project description:BackgroundScientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.ResultsSidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick.ConclusionsSidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that traditional single gene lists do not, particularly in areas such as interaction discovery.

Dataset Information

A modelling framework for improved design and decision-making in drug development.

Publications

A modelling framework for improved design and decision-making in drug development.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets