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WEBINAR SERIES: AI in the life sciences: exploring possibilities, inspiring change

Goudey, Benjamin; Trigos, Anna; Li, Maisie; de Lima Campos, Tulio; Salazar, Vinícius W.; Santos-Martin, Carlos; Mangiola, Stefano; Nguyen, Anh TN; Harms, Rebekah; Aquino, Yves Saint James; Claeys, Tine; Schwämmle, Veit

Abstract

This record collates training materials associated with the Australian BioCommons webinar series 'AI in the life sciences: Exploring possibilities, inspiring change' that took place between June - September 2025. Series description Join us for a series of webinars where we explore how Artificial Intelligence (AI) is shaping the future of life sciences! This series provides an accessible introduction to AI while giving direct access to experts and practical insights into real-world applications. Designed to inspire and help you recognise potential applications of AI in the life sciences, these webinars will spark new ways of thinking so that you can start applying AI in your work. The webinars include: A foundational session covering AI basics, its evolution, and why it matters for life sciences. Watch the recording here! Guest speaker sessions where leading experts from academia and industry share how AI is being applied in different domains Live Q&A to engage with speakers, ask questions, and participate in discussions Training materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Series metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Campos (PDF): a PDF copy of the slides presented by Dr Túlio de Lima Campos during the webinar. Li (PDF): a PDF copy of the slides presented by Dr Maisie Li during the webinar. Salazar (PDF): a PDF copy of the slides presented by Dr Vinícius W. Salazar during the webinar. Harms (PD): a PDF copy of the slides presented by Dr Rebekah Harms during the webinar. Veit (PDF): a PDF copy of the slides presented by Dr Veit Schwämmle during the webinar. Materials shared elsewhere: Recordings of all webinars in this series are available Australian BioCommons YouTube channel. Deciphering AI for the Life Sciences Dr Benjamin Goudey, Australian BioCommons Recording: https://www.youtube.com/watch?v=sbVzcrD-wko Slides: https://doi.org/10.5281/zenodo.15110330 Our journey incorporating AI into our cancer computational research Dr Anna Trigos, PeterMac Recording: https://youtu.be/vCkGbWuyLaQ?si=KLtjgdMs5sQscrq- Slides: https://doi.org/10.5281/zenodo.15770502 Towards Human-AI Collaboration in Genomics and Bioinformatics Dr Maisie Li, CSIRO A Journey into Binary Classification Challenges in AI Dr Túlio de Lima Campos, Oswaldo Cruz Foundation (Brazil) and University of Melbourne Recording: https://youtu.be/3Ge9aymRKRI?si=9Rg4sl1wWXIrkKmv Deep Learning Meets the Deep Sea: AI in Microbial Oceanography Dr Vinícius W. Salazar, Melbourne Bioinformatics AI-Driven Discovery and Therapeutic Innovation in Fungal and Bacterial Pathogenesis Dr Carlos Santos-Martin, University of Melbourne Recording: https://youtu.be/qXK7Uvf6Utk?si=15iSaeVkgnMa-nOC Improving the interpretability of AI models for cell biology and precision medicine Dr Stefano Mangiola, University of Adelaide Bridging pharmacology and AI: Accelerating GPCR drug discovery with deep learning Dr Anh TN Nguyen, Monash University Recording: https://youtu.be/-m0tvmNgFic?si=jBruJ3U4uSnUYeoa Ensuring equity in the integration of artificial intelligence in engineering biology Dr Rebekah Harms, UNSW Data equity and the challenges of diversifying datasets for artificial intelligence Dr Yves Saint James Aquino, University of Wollongong Recording: https://youtu.be/6bPY4Dquabs?si=YLl5PxNzoEdguR0J AI-readiness of proteomics data: challenges, applications, and future perspectives Tine Claeys, UGent An overview of deep learning methods to enhance proteomics data analysis Dr Veit Schwämmle, SDU Recording: https://youtu.be/qImAEHkXBKY?si=ItX-2af6Fyhy3rY9

Full text

Ensuring equity in the integration of artificial intelligence in engineering biology Rebekah Harms Team: Jackie Leach Scully, Rachel Ankeny, Aditi Mankad, Lucy Carter AI in engineering biology Engineering biology: ‘[…] the design, scaling and commercialisation of biology-derived products and services that can transform sectors or produce existing products more sustainably’ [1] AI bias can emerge at all stages of the development pipeline •Data collection → Algorithm design → Implementation [1] Department for Science, Innovation and Technology: National Vision for Engineering Biology. UK Government (2023) Systematic literature review Timespan: 2015-2024 Databases: Scopus/Web of Science ( "artificial intelligence" OR ai ) AND ( medic* OR health OR healthcare ) AND ( equit* OR inequit* OR equalit* OR inequalit* OR inclusi* OR bias* OR fair* OR unfair* OR disparit* OR justice* OR injustice* OR divers* ) 8,119 Abstracts screened 1,831 Articles screened 51 Articles reviewed Articles by medical field Articles by year Stakeholder interviews Scientists AI developers Healthcare practitioners Industry actors Ethics policymakers Database representatives Open-ended interviews to be conducted with stakeholders along the AI development pipeline Nine interviews conducted so far: •Scientists (n=6) •AI developers (n=1) •Healthcare practitioners (n=1) •Industry actors (n=1) Findings from stakeholder interviews Themes Quotes AI use widespread for routine tasks ‘Now I use a coding copilot […] and it saves me minutes to hours looking up stuff that I would eventually figure out […] and I get back to the job I actually like doing’ AI being used to conduct research ‘The only hope on the horizon is AI [in controlling cancer]’ Bias and inaccuracies a key issue ‘The moment you give a direction to your AI […] you bias it to some extent’ Findings from stakeholder interviews Themes Quotes AI just another tool ‘With any technology, like there’s positives and negatives’ Human expertise still important ‘I’m a firm believer that […] an AI tool shouldn’t replace a human […] the human still needs to bear the ultimate responsibility to make the final decision’ Lack of guidelines around AI use ‘I think it’s the wild west at the moment with regards to that [guidelines]’