AI in drug discovery is overhyped: examples from AstraZeneca, Harvard, Stanford
1) As someone who does NLP and AI for Evidence Based medicine [1] I can only agree. I build natural language processing tools, together with the team, for EBM. I have &#x2F;no&#x2F; idea what to do next. Please. Help me.<p>2) Rant: here&#x27;s the thing, we have SVMs, LSTM, BiLSTM-CRF, Knowledge Graphs, 28M articles, deploy infrastructure, tests, you know all the cool stuff. We can&#x27;t sell it. It&#x27;s PubMed this, PubMed that. There&#x27;s no breaking that spell. So instead of building a better search engine, we focused on better analytics. Is it cool, sure. Is it as good as all the KoL stuff from LexusNexis, nope. Medicine is &#x2F;hard&#x2F;, if you think your app is hard: medicine is &#x2F;harder&#x2F;. Am I trying to cover my ass, sure. But seriously, deal with everything being non-standard and proprietary for long enough and you&#x27;ll feel the same way. 80% of my job is saying &quot;no&quot; to people who aren&#x27;t going to pay in the first place (Sanofi, Novartis, etc). They don&#x27;t care. I&#x27;m just going to ride this out, throw some blockchain in somewhere where it makes absolutely 0% sense, call it a day. Seriously, NLP&#x2F;AI for medicine: it&#x27;s crap 100%.
And, I&#x27;m a &quot;senior developer&quot; with publications behind my ass on this. I don&#x27;t know what to do instead of riding the hype train. Seriously: anyone out there that knows what to do with 100M+ medical publications in a 100M+ knowledge graph, be my guest: I&#x27;d hire you in a heart beat. But it&#x27;s hard and there is nothing to be gained AFAIK.<p>[1]: <a href="http:&#x2F;&#x2F;growthevidence.com&#x2F;joel-kuiper&#x2F;" rel="nofollow">http:&#x2F;&#x2F;growthevidence.com&#x2F;joel-kuiper&#x2F;</a>