Drug discovery

Drug discovery

The process by which new candidate medications are discovered

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Machine learningMachine learning, artificial intelligence (AI), and other software developments have made it possible to increase the speed, cost, and overall effectiveness of the drug discovery process through enhancing pattern recognition. Thomas Chittenden, a team leader at the drug discovery company Wuxi NextCODE, commented on the role AI is playing in the drug discovery process in an interview with the scientific journal Nature in 2018 by saying:

Jason D. Rowley
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Clustered regularly interspaced short palindromic repeats (CRISPRCRISPR) technology gives drug discovery researchers the ability to alter sequences and expression levels of genes to help them identify therapeutic drug targets and test the therapeutic efficiency of drug candidates. CRISPR has become more useful in the drug discovery process as the cost of using CRISPR and DNA sequencing technologies has decreased due to technological and economies of scale improvements. CRISPR can play a role in several stages of the drug discovery process as outlined in the following diagram:

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Clustered regularly interspaced short palindromic repeats (CRISPR) technology gives drug discovery researchers the ability to alter sequences and expression levels of genes to help them identify therapeutic drug targets and test the therapeutic efficiency of drug candidates. CRISPR has become more useful in the drug discovery process as the cost of using CRISPR and DNA sequencingDNA sequencing technologies has decreased due to technological and economies of scale improvements. CRISPR can play a role in several stages of the drug discovery process as outlined in the following diagram:

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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CRISPR is used systematically during the target identification and validation process to knockout, inhibit, and alter the expression levels of certain genes. It helps researchers understand how genes and their expression can improve or diminish disease states, and identify and help better predict how drug candidates may produce beneficial or harmful patient outcomes. Both in vivo and in vitro studies are done using CRISPR technology to facilitate gene knockout and expression level studies in the drug discovery process.

Dawson Sewell
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Software

Artificial intelligence

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Selecting a clinical candidate

Selecting a clinical candidate

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Clustered regularly interspaced short palindromic repeats (CRISPR)

Clustered regularly interspaced short palindromic repeats (CRISPR) technology gives drug discovery researchers the ability to alter sequences and expression levels of genes to help them identify therapeutic drug targets and test the therapeutic efficiency of drug candidates. CRISPR has become more useful in the drug discovery process as the cost of using CRISPR and DNA sequencing technologies has decreased due to technological and economies of scale improvements. CRISPR can play a role in several stages of the drug discovery process as outlined in the following diagram:

Role of CRISPR in the stages of Drug Discovery.
Further reading

Title
Author
Link
Type
Date

How CRISPR Is Accelerating Drug Discovery

Brittany L. Enzmann, PhD, Ania Wronski, PhD

Web

January 11, 2019

How CRISPR is transforming drug discovery

Andrew Scott

Web

March 7, 2018

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Further reading

Title
Author
Link
Type
Date

Drug Discovery and Development: An Overview

Sandeep Sinha and Divya Vahora

Web

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Selecting a clinical candidate

Selecting a drug candidate for clinical trials typically need to demonstrate desirable properties in several areas before clinical trials begin. The drug candidate should show evidence of having the following favourable properties:

  1. Chemical
  2. Physiochemical
  3. Pharmacological
  4. Pharmacokinetic
  5. Safety and toxicity
Henry Ogolla
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Machine learning, artificial intelligence (AI), and other software developments have made it possible to increase the speed, cost, and overall effectiveness of the drug discovery process through enhancing pattern recognition. Thomas Chittenden, a team leader at the drug discovery company Wuxi NextCODEWuxi NextCODE, commented on the role AI is playing in the drug discovery process in an interview with the scientific journal Nature in 2018 by saying:

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Artificial intelligence

Software

Machine learning, artificial intelligence (AI), and other software developments have made it possible to increase the speed, cost, and overall effectiveness of the drug discovery process through enhancing pattern recognition. Thomas Chittenden, a team leader at the drug discovery company Wuxi NextCODE, commented on the role AI is playing in the drug discovery process in an interview with the scientific journal Nature in 2018 by saying:

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Overview of the drug discovery process

Identification of an unmet medical need

The drug discovery process begins with the identification of unmet medical needs through market analysis and input from patients, medical practitioners, therapeutic researchers, scientific conferences. The medical need must have a level of unsatisfactory treatment options to justify initiating the drug discovery process, or the potential of a novel drug may offer substantial advantages compared to existing treatments such as improved therapeutic efficiency, less adverse side-effects, better patient compliance, fewer drug interactions, and improvements in the overall patient quality of life.

After an unmet medical need is established the drug discovery process moves onto identifying potential drug targets to solve the unmet medical need through techniques such as phenotypic screening, genetic association, transgenic organisms, and medical imaging. Identifying unmet medical needs is an ongoing process of understanding available therapeutic treatment options, disease etiology, and epidemiology. This constant identification process produces an always changing analysis gap of the perceived value and potential of potential drug candidates leading to certain drug candidates taking priority over others to better address particular medical needs.

Dawson Sewell
Dawson Sewell edited on 8 Oct, 2020
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Drug discovery is the process by which new candidate medications are discovered. It combines the fields of medicine, biotechnology, chemistry, and pharmacology to create new safe and effective medications and treatments. Traditional approaches to drug discovery involve identifying medicinal properties and compounds in found in plants and other traditional medical remedies. Technological developments in software, artificial intelligence, biotechnology, medicinal chemistry, and manufacturing have widened the possibilities of drug discovery beyond traditional drug discovery methods.

Technologies

Artificial intelligence

Machine learning, artificial intelligence, and other software developments have made it possible to increase the speed, cost, and overall effectiveness of the drug discovery process through enhancing pattern recognition. Thomas Chittenden, a team leader at the drug discovery company Wuxi NextCODE, commented on the role AI is playing in the drug discovery process in an interview with the scientific journal Nature by saying:

AI is going to lead to the full understanding of human biology and give us the means to fully address human disease. The way we develop drugs and assess them in clinical trials will all come down to very sophisticated pattern recognition.
...

Drug discovery companies

Further reading

Title
Author
Link
Type
Date

How artificial intelligence is changing drug discovery

Nic Fleming

Web

May 30, 2018

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 Drug discovery

The process by which new candidate medications are discovered

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