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Discovery and Drug Repurposing

Vaishnavi Reddy

February 28, 2021

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Pharmaceutical research involves preliminary studies of around 5000-10000 chemical compounds, out of which 250 enter the pre-clinical testing stage to produce one new approved drug for human use. The overall process takes 10-15 years from discovery to marketing the final product. The product cycle starts with an array of public organizations that carry basic research projects in biochemistry, pharmacology, physiology, microbiology, etc. and publish them in various scientific and medical journals. Some notable knowledge bases widely used in drug discovery include the World drug index, MDL Drug Data Report, WOMBAT, AurSCOPE (Aureus Pharma, France), ChemBioBase (Jubilant Biosys, India), and GVKBIO database (GVKBio, India). These projects are pivotal in a unique understanding of natural substances and physiological processes rather than catering to a specific drug’s requirements. They comprise vital information that can enable private and other pharmaceutical players to identify potential new targets for drug discovery. The researchers validate these targets by studying disease association, bioactive molecules, cell-based models, protein interactions, signalling pathways analysis, and functional analysis of genes before they proceed to compound screening.

The pharmaceutical companies have colossal libraries of synthesized and natural chemical compounds that have been studied for decades. In the next step, the scientists try to match the identified targets with compounds by screening them for potential pharmacological effects and develop assays (testing systems) to evaluate the major effects of the compound on cellular, molecular and biochemical levels. Some even try to synthesize new compounds via processes such as structural activity relationship (SAR), computer-aided drug design, combinatorial chemistry, etc. In SAR, they synthesize a series of structurally related compounds and test each one of their capabilities to activate or block particular drug receptors by further establishing mathematical relationships between the chemical structure and drug activity. With advanced computers and sophisticated graphics software, scientists began designing new molecules and studying their potential interactions with receptors/enzymes before they were synthesized. Combinatorial chemistry is another approach that the pharmaceuticals devise that substantially cuts down the use of resources and duration by combining multiple blocks of compounds with a secondary and tertiary set of compounds parallelly giving rise to many more new compounds than the output of the traditional linear compound building process.

Most of these processes enter high throughput screening process (HTS), which uses robotics, data processing/control software, liquid handling devices, and sensitive detectors to rapidly conduct millions of pharmacological, chemical, and genetic tests. This eliminates hours of painstaking testing by scientists and accurately identifies active compounds, genes, or antibodies that affect human molecules. Molecules that fit the criteria are then evaluated and optimized to become lead compounds through the H2L (hit to lead) process. Following this, the selected components are further studied and modified in the Lead Optimisation (LO) process via experimental testing using ADMET tools (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and animal efficacy models to develop a successful drug candidate.

Similarly, drug repositioning has also acquired massive momentum in the last decade as it establishes new medical uses for already existing drugs such as approved, discontinued, shelved, and experimental drugs. Around 1/3rd of the recently approved drugs are repurposed, contributing to 25% of the pharmaceutical industry’s annual revenue internationally. The investment and duration of drugs’ development are also shortened to an enormous extent as most of the drugs are pre-approved or have verified pre-clinical models. Repurposing a drug only requires dose compatibility and efficacy testing as it primarily relies on an already known drug pharmacology. Furthermore, the drug community is moving swiftly towards a more data-driven, organized, systematic approach of drug reposition, which is significantly integrated with computational assistance in fields of molecular similarity approximations, signature matching of transcriptomic or proteomic data, structure-based virtual screens and, systematic analysis of electronic health records.

Due to the highly collaborative nature of drug development, there are multiple challenges associated with the associated procedures. Patent rights and some national/international legislation can prevent pharmaceutical companies from obtaining secondary patents for further medical uses. Limited data availability, accessibility, and varied data types pose multiple obstacles in data mining, integration, and manipulation. The primary goal of drug repositioning is to analyze and discover the therapeutic target of the drug of interest while simultaneously understanding its off-target effects, which is hugely facilitated by publicly accessible databases such as DrugBank, Potential Drug Target Database, Therapeutic Target Database, and SuperTarget. With widescale compound libraries and open-source drug databases surfacing in every country, both small and large-scale pharmaceutical players are given equal opportunities in drug repositioning. Moreover, the analysis of real-time data from health insurance claims, body health trackers, hospitals, and other medical devices has added new dimensions of research of similar drugs that outline drug effectiveness both physiologically and epidemiologically.

Subtl can enable all the research institutions and pharmaceutical companies to accelerate drug discovery and repositioning processes via intelligent document searching mechanisms. Fundamental understanding of compounds and screening can be performed much more efficiently by retrieving the exact results from various databases within moments and comparing a group of compounds based on the user-chosen criteria. Synthesis and modification of any compounds before HTS can also be expedited by using Subtl to benchmark them with structurally or functionally similar compounds and even design new compounds based on the same. Additionally, it can be directly institutionalized within all the HTS, ADMET, and other animal efficacy models to support information quality and accessibility at each of the million tests conducted. Any previous research and findings can be uploaded to Subtl, and the research teams can be given custom access to confidential information simultaneously protecting the associated IP rights and other limitations in a timely fashion. Subtl also eliminates the challenges of collaborative working by standardization of various documents using cognitive understanding and giving out simplified, accurate, and compact results for any query thereby promoting a synergistic drug research atmosphere globally.

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Vaishnavi Reddy

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