Ask the Experts: meet our artificial intelligence experts

In this ‘Ask the Experts’ feature, we explore the use of artificial intelligence in the drug discovery field. Keep an eye out over the next few weeks for our expert answers.

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Jun 18, 2019
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Following on from our look at computational chemistry in drug discovery in late 2018, we asked a group of experts what they think about the use of artificial intelligence (AI) in drug discovery; is AI really the solution to more efficient drug discovery? Find out more. 


Connor Coley

Connor Coley’s research interests are in how data science and laboratory automation can be used to streamline discovery in the chemical sciences. His work in the MIT Department of Chemical Engineering (MA, USA) has focused on the development of computational tools to assist chemical synthesis, including the data-driven synthesis planning program ASKCOS and in silico strategies for predicting the outcomes of organic reactions.

Ola Engkvist

Ola Engkvist completed his PhD in Computational Chemistry at the University of Lund (Sweden), after which he went on to complete his postdoctoral research at the University of Cambridge (UK) and the Czech Academy of Sciences (Prague, Czech Republic). He joined AstraZeneca in 2004, where he currently remains and leads the Discovery Sciences Computational Chemistry team within R&D BioPharmaceuticals, providing solutions for drug discovery.

Passionate about pushing the boundaries in the use of artificial intelligence and machine learning in drug discovery, a key focus for Engkvist has been building not only the team within R&D BioPharmaceuticals but also collaborating with external experts to advance innovation in drug design and synthesis.

In a pioneering collaboration with the University of Muenster (Germany), Engkvist and his team demonstrated the first application of recurrent Neural Networks to molecular design, which allows novel drug molecules to be designed using machine learning. These findings have been recently published in two highly-cited articles.

Mallikarjuna Rao Pichika

Mallikarjuna Rao Pichika is a Professor in Pharmaceutical Chemistry at the School of Pharmacy, International Medical University (Kuala Lumpur, Malaysia). At present, he is the Associate Dean (Research & Consultancy), School of Pharmacy looking after the research activities in the School. Pichika is also the Head for the Center of Excellence, ‘Bioactive Molecules & Drug Delivery’, Institute for Research, Development and Innovation (IRDI) at the International Medical University. His research specialization is in medicinal chemistry with a special emphasis on drug discovery & development.

Kit-Kay Mak

Kit-Kay Mak is a Lecturer in Pharmaceutical Chemistry at the International Medical University. Mak is the recipient of Wellcome Trust Fellowship from Wellcome Centre for Anti-infectives Research (Dundee, UK) and Artificial Intelligence Molecular Screen (AIMS) award from Atomwise (CA, USA). In addition, she was selected as one of the top three contestants in the BioSolveIT Scientific Challenge. Her research focus is in medicinal chemistry with special interest in artificial intelligence in drug discovery and development.


Questions:

  1. What impact has artificial intelligence already had on drug discovery
  2. How can artificial intelligence address some of the problems faced by drug discovery?
  3. What are some of the challenges in applying artificial intelligence in drug discovery? What needs to be done to overcome them?
  4. Is there too much hype surrounding the promise of artificial intelligence?
  5. What do the next 5—10 years look like for artificial intelligence? 

Do you use artificial intelligence in your work? Let us know your views and join the conversation today on RxNet, TwitterFacebook or LinkedIn


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RxNet

A network for the drug discovery and development community, Future Science Group

Your source for the latest news and views from the fields of drug discovery and medicinal chemistry.

1 Comments

Go to the profile of Ann Fonfa
Ann Fonfa 3 months ago

I heard two separate presentations on Watson, the AI that can judge cancer issues, primarily staging and supposedly treatments.  I asked both groups if Watson learned about NUTRITION.  I was told no.  What Watson does not know, means less value for the Patient population.  I speak as the founder/president of Annie Appleseed Project.  An all-volunteer cancer nonprofit.  I was diagnosed with breast cancer in Jan 1993.  And diagnosed with follicular lymphoma in Jan 2019.

Our focus is on complementary medicine (along with conventional treatment), lifestyle changes (in simple steps that anyone can implement) and holistic therapies as needed.  We gather and spread the evidence.