Use of big data in drug development for precision medicine

Abstract

Summary Drug development has been a costly and lengthy process with an extremely low success rate and lack of consideration of individual diversity in drug response and toxicity. Over the past decade, an alternative “big data” approach has been expanding at an unprecedented pace based on the development of electronic databases of chemical substances, disease gene/protein targets, functional readouts, and clinical information covering inter-individual genetic variations and toxicities. This paradigm shift has enabled systematic, high-throughput, and accelerated identification of novel drugs or repurposed indications of existing drugs for pathogenic molecular aberrations specifically present in each individual patient. The exploding interest from the information technology and direct-to-consumer genetic testing industries has been further facilitating the use of big data to achieve personalized Precision Medicine. Here we overview currently available resources and discuss future prospects.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

“…Using electronic databases of chemicals and protein targets and clinical data such as patient to patient variations in response to treatment, several strategies are being employed to reduce the cost of drug development and to increase the speed at which drugs are developed [ 193 ]. There are obvious challenges to the efficient development of drugs and these include the lack of models that can recapitulate the human body properly in terms of response to candidate compounds, the heterogeneity of individuals in terms of their response to candidate compounds and the inability to analyse biological processes properly during testing of candidate compounds [ 194 , 195 , 196 ].…”

“…A challenge to scientists using big data to inform drug development and testing is how to integrate a lot of information into a meaningful and manageable unit. For “omics” data to be meaningful and to revolutionise clinical medicine, clinical phenotype data has to be integrated with genomic, transcriptomic, proteomic and epigenomic data [ 33 , 193 , 209 ].…”

Technical Blossom in Medical Care: The Influence of Big Data Platform on Medical Innovation

“…With the development of information technology and the explosion of data, more and more studies are focusing on the application of big data in the medical and public health fields [15,17,19]. With the continuous penetration of the concept of big data, the academic circle has engaged in a profound discussion on its concept in recent years.…”

“…The mechanism to improve medical innovation is always a key issue in public health research. In recent years, with the influx of big data and artificial intelligence, more and more studies have been initiated on the impact of technological change, most of which are focused on the fields of basic medicine and public health [15][16][17]. The explosive growth of medical research as a result of the accumulation of knowledge and data has resonated not only with academics, but also with the funders of research and development [18].…”

Prediction of Potential Lead Molecules through Systematic Integration of Multi-omics Datasets - A Mini-Review

“…Size of big data ranges from petabytes(1 PB = 10 15 bytes) to exabytes (1 EB = 10 18 bytes), or even more [13][14][15].Even though the big data analysis is a hot topic today, the concept has evolved over many years ago in IT and R&D sector. Nextgeneration sequencing (NGS) and drug discovery are the two most popular areas of biological sciences which currently implement big data analysis in knowledge discovery [16][17][18].…”