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Artificial intelligence in drug discovery and development

Over the past few years, there has been a drastic increase in data digitalization in the pharmaceutical sector. However, this digitalization comes with the challenge of acquiring, scrutinizing and applying that knowledge to solve complex clinical problems. Machine learning and other technologies are expected to make the hunt for new pharmaceuticals quicker, cheaper and more effective. Artificial Intelligence (AI) has recently started to gear up its application in various sectors of Pharmaceutical Industry including drug discovery and development, drug repurposing, improving pharmaceutical productivity etc   thus reducing the human workload. Involvement of AI in the development of a pharmaceutical product can be imagined to give an aid rational drug design, assist in determining the right therapy for a patient including medicines and use it for future drug development. Artificial Intelligence has been proven to a progression in drug discovery and development. Machine learning is the

DRUG DISCOVERY

Drug discovery is the method through which new medicines are identified which has potential to become therapeutic agents. The process of drug discovery involves the identification of candidates, synthesis, characterization, screening and assays for therapeutic efficacy. The process of drug discovery is followed in the field of medical, biotechnology and pharmacology. Earlier, drugs were mostly found by identifying active ingredients from traditional medicines or by chance. Later, classical pharmacology was used to investigate  chemical libraries including small molecules, natural products, or  plant extracts, and find those with therapeutic effects. Since Human DNA was sequenced reverse pharmacology has found remedies to existing diseases through testing. But now , drug discovery involves screening hits, medicinal chemistry and optimization of hits to reduce potential drug side effects. The efficacy and metabolic stability of drugs are also improved. Steps involve in Drug Discovery

PHARMACOVIGILANCE

  Pharmacovigilance also known as drug safety, is a broad term that describes the collection, analysis, monitoring and prevention of adverse effects in drugs and therapies. Pharmacovigilance referred to the activities involved in the detection, assessment, understanding and prevention of adverse effects or any other problems. All drugs have the capacity to cause adverse effects and no drug is completely safe. Medication safety is of particular concern for dermatologists, as most treatment indications involve diseases that are not life-threating and are often chronic, requiring years of medical therapy. The underlying objectives of pharmacovigilance are to prevent harm from adverse reactions in humans that arise from the use of health products within or outside the terms of marketing authorization and in relation to the life cycle of these health products. The PV system team obtains valuable additional information, building up the scientific data contained in the original report and m

PHARMACOGENETICS

  Pharmacogenetics is a science that shows the role of individual’s genetic makeup in the work of medicines and about the side effects which are likely to occur. It refers to the genetic differences in metabolic pathway which effect individual responses to drug. The advantages of pharmacogenetics includes safer drugs, appropriate dose, better vaccination, advance screenings, and better medicines. The field of pharmacogenetics began with a focus on drug metabolism and extended to drug disposition including drug absorption, distribution and excretion.   The main goal of pharmacogenetics is to predict patients genetic response to a specific drug as a means of delivering the best possible medical treatment.   By predicting the drug response to a specific drug as a means of delivering the best possible medical treatment.   Pharmacogenetics was first used in relation to phenotypic variation in metabolism and response to certain drugs. As gene cloning advanced to sequencing of the entire huma