Technological Strides in Drug Discovery Informatics Market to Speed up Drug Development and Their Efficacy

Drug Discovery Informatics

Pharma Industry Pin Tall Hopes on Informatics for New Candidate Screening

Drug discovery is a cost-intensive and time-intensive process, making pharma companies constantly scrambling for reducing the timeline and meeting the unmet need of patient populations. Perhaps more important than anything else is ensuring that new drug candidates show good success rates. A large part of the imperative is due to massive development costs pharma companies have at stake across the pipeline. Balancing the dichotomy of intended efficacy and reaping expected RoI in drug discovery has been a lingering concern for pharma companies and healthcare companies and patients at large.

Consider a statistics revealed in a recent article in the NCBI, it costs approximately US$800 million to bring a drug to market. The projection that this cost is likely to increase by 100% every five years is more concerning. Add to this, there are regulatory and administrative hurdles drug makers face in all key markets. For instance, out of 5,000 compounds that are put under pre-clinical testing, only one receives final approval, highlighting the desperation drug companies face. The evolution of informatics raised hopes to circumvent these challenges over the years.

Drug Discovery Processes and Informatics Can’t be Isolated

Computer-assisted cutting-edge computational techniques have added value across the entire drug discovery and development chain, a key trend propelling the evolution of drug discovery informatics market. Design of novel drug target, identification of promising drug candidates, characterization of side effects, and predicting and reducing the chances of drug resistance are all witnessing growing contribution of drug informatics.

Drug discovery informatics have massively influenced lead and target discovery, and a case in point is the use of computational analysis for developing lead synthesis pathways.

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Machine Learning Invigorates Development of Novel Targets

Over the years, machine learning and deep learning algorithms have been increasingly incorporated in drug discovery. The trend is evident from the growing adoption of multiple software/web-tools by drug companies. The algorithms have helped shed light on crucial aspects such as drug-protein interaction, drug efficacy, bioactivity of molecules, and safety biomarkers.

Contract Research Organizations Leverage High Through-put Computational Systems

Pharma and biotech companies especially in developed countries have grown their research spending by collaborating with contract research organizations (CROs). It is here that the business prospect of drug discovery informatics tools and technologies is massive. The incredible avenues make technology companies and IT service providers eye vast revenue streams in the drug discovery informatics market.

Bioinformatics Change Face of Drug Development for Disease Biology

The ‘-omics’ methodologies are making rapid penetration in drug discovery and development, underpinning a vast canvas for players in the drug discovery market. Informatics integrated with new approaches functional genomics have advanced the scope of genome mapping and sequencing. For instance, the emerging area of proteomics and transcriptomics has helped drug companies predict the toxicity of drugs with greater accuracy, thereby accelerating the drug discovery. The growing penetration of large-scale methodologies has boosted the growth prospects drug discovery informatics market.

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Omics Technologies Advance Scope of Precision Medicine and Therapies for Genetic Diseases

The drive for personalized medicine is a key trend that has propelled the market to reach new height. The Big Data from genomics, transcriptomics, proteomics, and other pan-omics have been simplified by leveraging ML algorithms.

Use of bioinformatics platforms has helped facilitate drug discovery in diseases typically that have high healthcare burden: cancers, neurological disorders, and chronic diseases afflicting the elderly. Use of the currently available bioinformatics tools and software enables drug companies to speed up discovery of better-targeted therapeutic agents in Alzheimer’s disease (AD). Growing number of pharmacogenomics-guided clinical trials has helped drug companies achieve the duo of shortening of the drug development process and rein in costs. Another area that have been attracted drug makers are genetic diseases. They have leveraged advanced bioinformatics to gain access to genomic sequence and exome data. Further, the growing relevance of target-based drug discoveries in human diseases particularly caused by pathogens has spurred investments in the drug discovery informatics market.

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