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X-WR-CALNAME:AWS AI League: Drug Discovery Challenge
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UID:aws-ai-league-drug-discovery-challenge@aiweek.boston
DTSTAMP:20260828T192128Z
DTSTART;TZID=America/New_York:20261002T090000
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SUMMARY:AWS AI League: Drug Discovery Challenge
DESCRIPTION:Overview\n\nFine-tune a Small Language Model (SLM) like Amazo
 n Nova Micro (via Amazon SageMaker AI) for drug discovery — identify ther
 apeutic targets and predict molecular properties with higher accuracy tha
 n what's possible with frontier-scale models\, and at lower costs.\n\nYou
 r fine-tuned SLM can either integrate multi-modal data to discover diseas
 e-specific targets\, or predict molecular properties like permeability gi
 ven a molecule's SMILES string — the same categories that determine wheth
 er a drug candidate survives to the clinic.\n\nThis follows the same appr
 oach used by Insilico Medicine (TargetPro) and Nimbus Therapeutics (Novus
  model) on AWS: supervised fine-tuning on thousands of labeled multi-moda
 l data\, then iterating on prompts\, data mixing\, and training strategy 
 to push accuracy higher.\n\nYou can team up with others to prepare traini
 ng data\, configure fine-tuning jobs on SageMaker AI\, and submit predict
 ions to an automated evaluation pipeline that scores against experimental
  measurements in real time. Sample datasets like TargetBench and ChEMBL i
 n JSONL Q&A pairs will be provided\, and you can bring your own datasets 
 as well. The team with the most accurate predictions wins up to $5K in AW
 S credits.\n\nAgenda\n\n9:00 AM – 9:30 AM | Breakfast & Networking\nGrab 
 coffee and breakfast\, meet fellow builders\, founders\, and Amazonians. 
 Setup AWS Workshop Studio environment plus Amazon Quick Desktop\, and a w
 alkthrough of the day's format.\n\n9:30 AM – 11:30 AM | Build Starts\nHan
 ds-on build sprint: use Amazon Quick to prepare datasets for model fine t
 uning\; take advantage of serverless model fine tuning capability on Amaz
 on SageMaker AI to develop your customized model. Deploy your best model 
 to Amazon Bedrock. Use Amazon Quick Desktop as your scientific workbench 
 to interact with your own model for competitive intelligent analysis.\n\n
 11:30 AM – 12:00 PM | Leaderboard Showcase\nSubmit your customized model 
 on pre-built leaderboard — we will evaluate the model capability against 
 certain tasks. Winners are rewarded with AWS credits and invited to showc
 ase your models to AWS leadership.\n\nWhat You'll Walk Away With\n- A fin
 e-tuned model you built\, hands-on experience with Amazon SageMaker AI\, 
 and potential prizes up to $5K in AWS credits.\n\nPrizes\n\nCategory: Tar
 get Identification\n- 1st Place: $3\,000 in AWS Promotional Credits + AWS
  AI League Championship invitation\n- 2nd Place: $2\,000 in AWS Promotion
 al Credits\n- 3rd Place: $500 in AWS Promotional Credits\n\nCategory: Mol
 ecular Property Prediction\n- 1st Place: $3\,000 in AWS Promotional Credi
 ts + AWS AI League Championship invitation\n- 2nd Place: $2\,000 in AWS P
 romotional Credits\n- 3rd Place: $500 in AWS Promotional Credits\n\nFull 
 contest terms and conditions: https://pages.awscloud.com/rs/112-TZM-766/i
 mages/BostonAIWeek_Contest%20Terms%20and%20Conditions%20%28Life%20Science
 %20R%26D%20Hackathon%29.pdf
LOCATION:AWS Office BOS17 Level 1\, Room 1.101\n27 Melcher St\, Boston\, 
 MA 02210\nBoston\, MA 02210\, 27 Melcher St\, Boston\, MA 02210
URL:https://aiweek.boston/schedule/aws-ai-league-drug-discovery-challenge
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