4.7 • 53 Ratings
🗓️ 23 March 2023
⏱️ 39 minutes
🧾️ Download transcript
Covid-19 unleashed a wave of medical and pharmaceutical research and innovation across the world. In India, the government launched the Drug Discovery Hackathon, an initiative designed to bring together expertise in fields ranging from biotechnology, pharmaceuticals, machine learning and virology to discover new drugs that could help thwart the pandemic.
One team that took part was from Thoughtworks India. In this episode of the Technology Podcast, two of the members — Pooja Arora and Justin Jose — talk to Rebecca Parsons and Ashok Subramanian about a number of projects they worked on during the hackathon. Among other things, they explain how they used reinforcement learning to improve the efficacy of potential drugs in tackling what was, at the time, a virus that was only partially understood.
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0:00.0 | Hello, everyone. |
0:09.4 | Welcome to the ThoughtWorks Technology podcast. |
0:12.6 | My name is Rebecca Parsons. |
0:14.1 | I'm one of your recurring co-hosts, and I'm with my colleague, Ashok. |
0:23.7 | Ashok, you want to introduce yourself? Hello, everyone. |
0:25.6 | I am Ashok, one of your regular co-hosts of this podcast. |
0:30.4 | And I'm delighted to be joining and discussing a very, very interesting topic today. And we are joined by two of our colleagues from ThoughtWorks India, |
0:44.3 | Pugia Aurora and Justin Joes. |
0:48.3 | And we are here to talk about using reinforcement learning for drug design. Welcome, Pugia. |
0:55.3 | Welcome, Justin. |
0:57.2 | Thanks, Rebecca. |
0:59.3 | So this project came about as a result of a hackathon, if I understand. |
1:06.4 | Can you tell me a little bit more about the hackathon? |
1:09.2 | Sure. |
1:10.5 | So this hackathon came up right in the middle of the COVID-19 crisis in 2020, where the world was fighting COVID |
1:20.5 | and the scientific world was figuring out ways how to control COVID. |
1:25.7 | That is the time where government of India launched the drug discovery hackathon. |
1:31.7 | And as a part of it, there were three tracks to it. |
1:34.9 | One was fighting in the, fighting a few of the COVID aspects. |
1:40.6 | The another track was to build tools and algorithms that will help in the current COVID-19 crisis |
1:47.9 | was also thinking from a future pandemic perspective and the another track was for any other moonshots |
1:54.8 | so we participated majorly in in track to to build tools and algorithms frameworks for fighting such pandemics. |
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