ASSESSING THE IMPACT OF PREDICTIVE BIOSIMULATION ON DRUG DISCOVERY AND DEVELOPMENT

2003 ◽  
Vol 01 (01) ◽  
pp. 169-177 ◽  
Author(s):  
SETH MICHELSON
Keyword(s):  
Mathematical Modeling ◽  
Drug Discovery ◽  
Laboratory Research ◽  
Pharmaceutical Companies ◽  
Drug Discovery And Development ◽  
Proteomic Data ◽  
Technical Advances ◽  
Potential Impact ◽  
The Impact ◽  
Major Data

Systems biology is creating a context for interpreting the vast amounts of genomic and proteomic data being produced by pharmaceutical companies in support of drug development. While major data collection efforts capitalize on technical advances in miniaturization and automation and represent an industrialization of existing laboratory research, the transition from mental models to predictive computer simulations is setting the pace for advances in this field. This article addresses current approaches to the mathematical modeling of biological systems and assesses the potential impact of predictive biosimulation on drug discovery and development.

A Role for Virtual Biotechnology Companies in Drug Discovery and Development?

2013 ◽  
Vol 19 (3) ◽  
Author(s):  
Dianne Nicol ◽  
Johnathon Liddicoat ◽  
Christine Critchley
Keyword(s):  
Drug Discovery ◽  
Business Model ◽  
Early Stage ◽  
Policy Implications ◽  
Pharmaceutical Companies ◽  
Virtual Model ◽  
Journal Articles ◽  
Drug Discovery And Development ◽  
Biotechnology Companies ◽  
Novel Method

The orthodox business model of many drug discovery and development companies centres on adding value to early-stage discoveries prior to engaging with large pharmaceutical companies to bring products to market. Anecdotal observations suggest some companies are moving to a ‘virtual’ business model - instead of employing in-house scientists, a skeletal management team runs the company and out-sources all research and development. This article presents a novel method to determine whether companies are virtual, based on author bylines in peer-reviewed journal articles. Applying this method to Australian companies in this sector, the size of the cohort identified as virtual was much larger than anticipated, around 52%. The accuracy of this method has been verified statistically using interview data. This article discusses the value and limitations of this method, positing that it can be used to analyse industry and policy implications that may result from widespread adoption of the virtual model

The impact of molecular biology on drug discovery

2006 ◽  
Vol 34 (2) ◽  
pp. 313-316 ◽  
Author(s):  
G.P. Belfield ◽  
S.J. Delaney
Keyword(s):  
Drug Discovery ◽  
Molecular Biology ◽  
Clinical Efficacy ◽  
Drug Targets ◽  
Safety Data ◽  
Vital Role ◽  
Drug Discovery And Development ◽  
New Drug ◽  
Whole Process ◽  
The Impact

The discipline of molecular biology has become increasingly important in recent times for the process of drug discovery. We describe the impact of molecular biology across the whole process of drug discovery and development, including (i) the identification and validation of new drug targets, (ii) the development of molecular screens to find new candidate drugs, and (iii) the generation of safety data and competences leading to enhanced clinical efficacy. We also speculate on emerging developments in drug discovery where it seems likely that molecular biology will play an even more vital role in the generation of future therapies.

A Perspective on Synthetic Biology in Drug Discovery and Development—Current Impact and Future Opportunities

2021 ◽  
pp. 247255522110006
Author(s):  
Florian David ◽  
Andrew M. Davis ◽  
Michael Gossing ◽  
Martin A. Hayes ◽  
Elvira Romero ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Synthetic Biology ◽  
Value Chain ◽  
Genome Organization ◽  
Data Science ◽  
Target Validation ◽  
Drug Discovery And Development ◽  
Global Impact ◽  
Current Impact ◽  
The Impact

The global impact of synthetic biology has been accelerating, because of the plummeting cost of DNA synthesis, advances in genetic engineering, growing understanding of genome organization, and explosion in data science. However, much of the discipline’s application in the pharmaceutical industry remains enigmatic. In this review, we highlight recent examples of the impact of synthetic biology on target validation, assay development, hit finding, lead optimization, and chemical synthesis, through to the development of cellular therapeutics. We also highlight the availability of tools and technologies driving the discipline. Synthetic biology is certainly impacting all stages of drug discovery and development, and the recognition of the discipline’s contribution can further enhance the opportunities for the drug discovery and development value chain.

scholarly journals Redesigning antidepressant drug discovery

2014 ◽  
Vol 16 (1) ◽  
pp. 5-7
Keyword(s):  
Drug Discovery ◽  
Animal Models ◽  
Psychiatric Disorders ◽  
Antidepressant Drug ◽  
Diagnostic Process ◽  
Pharmaceutical Companies ◽  
Drug Discovery And Development ◽  
Drug Candidates ◽  
Rapid Transfer ◽  
Efficacy Studies

Antidepressant drug discovery and development have been put on hold by many pharmaceutical companies. The main reason for this is the negative efficacy studies with novel specific drugs. Here I argue that the main obstacles are the absence of gene tests and biomarkers as an integral part of a diagnostic process. Further, too much emphasis has been put on validating drug candidates in animal models of psychiatric disorders. A more rapid transfer of drug candidates into human research is necessary to overcome current obstacles that prevent the discovery of next-generation antidepressants.

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