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Astraea uses a fully automated clinical biostatistics process to shorten the new drug approval cycle to just a few days

MeNews
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AIMPACT News, May 15 (UTC+8), Astraea is an AI-native platform focused on automating the biostatistics processes in clinical trials. The platform automatically generates CDISC-compliant SDTM and ADaM datasets, TFLs (tables, figures, and listings), and FDA-ready outputs by inputting raw clinical data, trial protocols, and research metadata. According to customer feedback, traditional processes typically take 9 months and involve a team of 5-10 people, while Astraea can reduce this process to just a few days. Currently, the platform focuses on oncology and rare disease research. Co-founders Joshua Wang (CEO) and Sanmay Sarada (CTO) are both from Stanford, with experience in AI systems and clinical data infrastructure. The platform has received support from Y Combinator. (Source: InFoQ)
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GateUser-a4680931
· 10h ago
Tumors and rare diseases are indeed the most complex fields in clinical data, and the entry point is very precise.
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PositionLikeACat
· 10h ago
Stanford background + YC endorsement, team composition maximized
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DrawTheCandlestickChartIn
· 10h ago
The combination of names Joshua Wang and Sanmay Sarada sounds quite academic.
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GateUser-7cb48814
· 10h ago
CDISC compliance automatic output, which for pharmaceutical companies saves not just time costs
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PuppyLooksAtTvl
· 10h ago
Compressing from 9 months to just a few days—such a leap in efficiency is truly astonishing. Are biostatisticians about to become unemployed?
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SeaSaltMarketMakingNotes
· 10h ago
The tracks that YC is betting on are getting more and more hardcore.
View OriginalReply0

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