This year, we combined the MIDD symposium and the MACC conference due to our recent move to the new chemistry building on 2000 E. Kenwood Blvd. The title of the MIDD MACC conference was Artificial Intelligence in Analytical Chemistry and Drug Discovery. The conference took place on 6th – 7th of December. On Friday, we started with keynote speaker Abhishek Pandey, who is Global Lead & Principal Research Scientist at AbbVie. His talk titled AI in Drug Discovery: An AbbVie perspective focused on the application of machine learning in the preclinical development of new drug candidates.
At AbbVie, the application of AI is relatively new bringing together medicinal chemists and pharmacologists with computational scientists. The wealth of AbbVie data is particularly amendable to the application of AI.
In the evening, MIDD director Dr. Arnold gave a short introduction about the MIDD and opened the floor to a discussion about regional drug discovery, entrepreneurship, the role of startup companies and how students can be involved in this process.
A lively discussion was focused on how especially students on US visas have limited opportunities to commercialize their ideas. We also discuss possible common interests between the MIDD and AbbVie.
The next day started with a presentation of renown scientist Lloyd Smith from UW Madison giving us a summary of the many programs that are ongoing in his lab.
He introduced the term proteoform to better describe the complexity of variation of proteins stemming from a single gene. This includes among other splice variants and PTM. Professor Smith is on the forefront of protein research using top-down analysis approaches with his collaborator Neil Kelleher.
His presentation was followed by Dr. Mark Ciaccio, who is the Principal AI Data Scientist for Global Therapeutics at AbbVie.
His talk gave an elegant introduction of AI followed by the application of AI to generate phase II clinical reports. Another example was the application of AI to generate legal documents that are understandable for the general public.
Professor Guowei Wei from Michigan State University took the stage to describe several examples of how AI can be used as a prediction tool.
For example, he was able to predict the mutations of the spike protein of the corona virus that will help us the future to develop vaccines in time. Other examples were AI supported topological analysis to better predict protein ligand interactions.
Hannah Wayment-Steele from UW Madison turned our attention to nuclear magnetic resonance, a technique that has been used to elucidate protein structures.
With NMR, proteins can be studied in real time and the analysis can tell us about the dynamic movement of specific regions. These regions won’t give us a signal and databases can be used to support machine learning to identify these regions for hundreds of proteins.
During our lunch break, more than 25 graduate and undergraduate students presented their work in the atrium of the new chemistry building.
Contributions from several local institutions showed a broad range of programs focused on analytical chemistry, drug discovery and computational approaches.
In the afternoon, Dr. Chris Witzigmann from MilliporeSigma introduced their new synthesis tool call SYNTHIA that is applied machine learning to enable scientist to identify new synthesis pathways to generated novel compounds.
Millipore gave workshop attendees online access to explore this tool during and after the workshop. This was followed by Shimadzu employee Dr. Nivesh Mittal focusing on the AI supported aspects of the LabSolution method development package that support a rapid identification of optimized methods to save development and run time.
Finally, Professor Prasenjit Guptasarma highlighted research that is ongoing in his lab followed by introducing of basic aspects of artificial intelligence with outstanding scientific examples.
He transitioned to discuss some ethical aspects and possible future directive of AI. This sparked a dynamic discussion about the pros and cons of AI and the responsibility of scientists developing new tools, especially in the area of generative AI and unsupervised machine learning.
Overall, more than one hundred scientists attended the MIDD MACC 2024 conference attracting undergraduate students from UWM and beyond. We are glad that the MIDD has become a renown institute that supports education, outreach and research collaboration with local institutions and industries. The event was sponsored in part by the Department of Chemistry and Biochemistry, MIDD member Steve Weitman, Ereztech, Shimadzu, and the George Keulks Memorial Lecture Fund.