Exclusive Chemaxon Interview Released - Sponsor at AI in Drug Discovery Conference 2022
SMi Reports: Chemaxon release an interview prior to joining the SMi’s 3rd Annual AI in Drug Discovery Conference on 14-15 March 2022 in London as a key sponsor.
London, United Kingdom, March 07, 2022 --(PR.com)-- In less than 2 weeks time, SMi's 3rd Annual AI in Drug Discovery Conference will be taking place on bringing together senior experts from Principal Scientists, Heads of Business Development, CEO and VP's in the AI in drug discovery field.
SMi Group are delighted to release a sponsor focused speaker interview with Akos Tarcsay, Product Manager, Chemaxon Ltd ahead of the conference.
To view the full interview please visit http://www.ai-indrugdiscovery.com/PR4, click on the "download centre" and then view "sponsor speaker interview - Chemaxon"
About Akos Tarcsay
Akos is the Product Manager of Calculators and Discovery Tools at Chemaxon, a leading software solutions and services provider for chemistry and biology. His team is responsible for delivering a wide range of high-quality phys-chem predictions, structural and topological descriptors, and clustering methods. Recently the team is active in the field of streamlining machine learning to provide access to predictions built on local datasets.
Akos has a Ph.D. in computational chemistry from Budapest University of Technology and Economics. He has more than 10 years of industry experience in cheminformatics and drug design obtained at Gedeon Richter Plc and Chemaxon.
An excerpt from the exclusive interview with Akos Tarcsay:
The AI in Drug Discovery market has matured greatly over recent years, what key differences have you noticed in the last year regarding significant developments?
“AI has become available for wider audiences by making machine learning easier to manage. Integration and MLOps developed significantly, making the ecosystem more robust, reproducible and stable. Techniques available in the scientific domain for a while are now closer to users who can harness the benefits of machine learning. In the last year generative modelling approaches have become standard to be applied in drug discovery settings.”
What do you see as the greatest challenge for you to overcome personally in the field of drug discovery at the moment?
“The perception about the results of machine learning. This is a cultural change; consumers of the AI model results are to be educated on the benefits and possible limitations of the model to avoid confusion and distraction.”
What area of drug discovery do you work within, and how have AI approaches helped in moving the discovery process forward?
“I am working with predictive modelling for on-targets and of targets in the field of pre-clinical optimization. ADMET predictions are one of the areas I am especially interested in. During the last year, I have built cardiotoxicity models. We are a software solution provider company and we help drug discovery teams in their endeavour to rank ideas and find high-quality synthesis candidates using data and predictions.
“The final goal is to increase the efficiency of drug discovery when balancing attributes and identifying successful drug candidates.”
Akos will be speaking at AI in Drug Discovery Conference on “Converting Data To Project Team Insights” on day one, covering:
• Building machine learning models for large number of targets
• Demonstration of use cases from ADMET predictions: hERG and penetration models
• Overarching review of challenges from data to actionable predictions
• Leveraging the power of predictions in integrated design system
Latest Attendees registered who will be attending the conference in less than 2 weeks include:
AI for Good Foundation, Astex Pharmaceuticals, AstraZeneca, Basecamp Research, Bayer AG, Benevolent AI, Boehringer Ingelheim, Cancer Research UK, CAS, CHARM Therapeutics, CIHI, Cresset Group, DISCNGINE, Envisagenics, Exscientia, GB Sciences, Genentech, GSK, Healx Limited, KSM, leadXpro AG, Merck, MultiOmic Health, Pfizer, Servier Pharmaceuticals, Sick Kids Childrens Hospital, Takeda, Verge Genomics, World Health Organization (WHO) and many more.
If you wish to join the conference you can register your place by visiting http://www.ai-indrugdiscovery.com/PR4
Sponsored by: Chemaxon, Optibrium and Schrödinger
Interested in sponsoring, exhibiting or speaking at this event? Contact Andrew Gibbons, Sales Manager, on +44 (0) 20 827 6156 or email agibbons@smi-online.co.uk
For media enquiries or to enquire about a press pass, contact Simi Sapal, Head of Marketing on +44 (0) 20 7827 6162 or ssapal@smi-online.co.uk
SMi’s 3rd Annual AI in Drug Discovery Conference
Conference: 14 – 15 March 2022
London, UK
http://www.ai-indrugdiscovery.com/PR4
#SMiAIinDrugDis
About SMi Group: Established since 1993, the SMi Group is a global event-production company that specializes in Business-to-Business Conferences, Workshops, Masterclasses and online Communities. We create and deliver events in the Defence, Security, Energy, Utilities, Finance and Pharmaceutical industries. We pride ourselves on having access to the world’s most forward-thinking opinion leaders and visionaries, allowing us to bring our communities together to Learn, Engage, Share and Network. More information can be found at http://www.smi-online.co.uk
SMi Group are delighted to release a sponsor focused speaker interview with Akos Tarcsay, Product Manager, Chemaxon Ltd ahead of the conference.
To view the full interview please visit http://www.ai-indrugdiscovery.com/PR4, click on the "download centre" and then view "sponsor speaker interview - Chemaxon"
About Akos Tarcsay
Akos is the Product Manager of Calculators and Discovery Tools at Chemaxon, a leading software solutions and services provider for chemistry and biology. His team is responsible for delivering a wide range of high-quality phys-chem predictions, structural and topological descriptors, and clustering methods. Recently the team is active in the field of streamlining machine learning to provide access to predictions built on local datasets.
Akos has a Ph.D. in computational chemistry from Budapest University of Technology and Economics. He has more than 10 years of industry experience in cheminformatics and drug design obtained at Gedeon Richter Plc and Chemaxon.
An excerpt from the exclusive interview with Akos Tarcsay:
The AI in Drug Discovery market has matured greatly over recent years, what key differences have you noticed in the last year regarding significant developments?
“AI has become available for wider audiences by making machine learning easier to manage. Integration and MLOps developed significantly, making the ecosystem more robust, reproducible and stable. Techniques available in the scientific domain for a while are now closer to users who can harness the benefits of machine learning. In the last year generative modelling approaches have become standard to be applied in drug discovery settings.”
What do you see as the greatest challenge for you to overcome personally in the field of drug discovery at the moment?
“The perception about the results of machine learning. This is a cultural change; consumers of the AI model results are to be educated on the benefits and possible limitations of the model to avoid confusion and distraction.”
What area of drug discovery do you work within, and how have AI approaches helped in moving the discovery process forward?
“I am working with predictive modelling for on-targets and of targets in the field of pre-clinical optimization. ADMET predictions are one of the areas I am especially interested in. During the last year, I have built cardiotoxicity models. We are a software solution provider company and we help drug discovery teams in their endeavour to rank ideas and find high-quality synthesis candidates using data and predictions.
“The final goal is to increase the efficiency of drug discovery when balancing attributes and identifying successful drug candidates.”
Akos will be speaking at AI in Drug Discovery Conference on “Converting Data To Project Team Insights” on day one, covering:
• Building machine learning models for large number of targets
• Demonstration of use cases from ADMET predictions: hERG and penetration models
• Overarching review of challenges from data to actionable predictions
• Leveraging the power of predictions in integrated design system
Latest Attendees registered who will be attending the conference in less than 2 weeks include:
AI for Good Foundation, Astex Pharmaceuticals, AstraZeneca, Basecamp Research, Bayer AG, Benevolent AI, Boehringer Ingelheim, Cancer Research UK, CAS, CHARM Therapeutics, CIHI, Cresset Group, DISCNGINE, Envisagenics, Exscientia, GB Sciences, Genentech, GSK, Healx Limited, KSM, leadXpro AG, Merck, MultiOmic Health, Pfizer, Servier Pharmaceuticals, Sick Kids Childrens Hospital, Takeda, Verge Genomics, World Health Organization (WHO) and many more.
If you wish to join the conference you can register your place by visiting http://www.ai-indrugdiscovery.com/PR4
Sponsored by: Chemaxon, Optibrium and Schrödinger
Interested in sponsoring, exhibiting or speaking at this event? Contact Andrew Gibbons, Sales Manager, on +44 (0) 20 827 6156 or email agibbons@smi-online.co.uk
For media enquiries or to enquire about a press pass, contact Simi Sapal, Head of Marketing on +44 (0) 20 7827 6162 or ssapal@smi-online.co.uk
SMi’s 3rd Annual AI in Drug Discovery Conference
Conference: 14 – 15 March 2022
London, UK
http://www.ai-indrugdiscovery.com/PR4
#SMiAIinDrugDis
About SMi Group: Established since 1993, the SMi Group is a global event-production company that specializes in Business-to-Business Conferences, Workshops, Masterclasses and online Communities. We create and deliver events in the Defence, Security, Energy, Utilities, Finance and Pharmaceutical industries. We pride ourselves on having access to the world’s most forward-thinking opinion leaders and visionaries, allowing us to bring our communities together to Learn, Engage, Share and Network. More information can be found at http://www.smi-online.co.uk
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SMi Group
Simi Sapal
+44 (0) 20 7827 6162
http://www.ai-indrugdiscovery.com/PR4prcom
Simi Sapal
+44 (0) 20 7827 6162
http://www.ai-indrugdiscovery.com/PR4prcom
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