Search results for raminderpal+singh - 31 results

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The predictive validity crisis: Pharma’s productivity paradox – Part II

24 October 2025 | By Dr Jack Scannell (CEO of Etheros Pharmaceuticals Corp), Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

Part II shows that the predictive validity crisis can be solved by rethinking how the industry chooses models, measures outcomes and integrates systems. Success stories from Vertex, Regeneron and AstraZeneca illustrate how aligning biology, measurement and strategy can reverse decades of declining productivity.

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Scientific workflow for hypothesis testing in drug discovery: Part 2 of 3

14 January 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers), Nina Truter

In part two of the step-by-step scientific workflow for drug discovery series, Dr Raminderpal Singh and Nina Truter describe the functions of the workflow previously outlined and include key considerations.

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The predictive validity crisis: Pharma’s productivity paradox – Part I

14 October 2025 | By Dr Jack Scannell (CEO of Etheros Pharmaceuticals Corp), Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

Drug discovery now costs 100 times more per FDA-approved drug than in 1950, despite vast advances in biology and computing. The core problem is the collapse of predictive validity in preclinical models, which sits at the heart of pharma’s productivity paradox.

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Large language models: now more affordable and reliable than ever

24 February 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

In this article, Dr Raminderpal Singh explores the transformative impact of the Deepseek R1 open-source large language model on drug discovery.  Its potential offers exciting opportunities for both scientists and software developers, marking a significant advancement for the life sciences community.

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Scientific workflow for hypothesis testing in drug discovery: Part 1 of 3

6 December 2024 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers), Nina Truter

Explore the step-by-step scientific workflow behind drug discovery, from formulating hypotheses to analysing data, ensuring accurate and reliable results.

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Beyond the hype: a veteran’s honest assessment of AI in drug discovery – Part 3

28 August 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

AI is starting to transform drug discovery, but progress is still slow and big challenges remain. Thibault Géoui explores the gaps, hurdles and breakthroughs needed before it can truly change pharma R&D.

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Beyond the hype: a veteran’s honest assessment of AI in drug discovery – Part 2

21 August 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

Thibault Géoui explains why AI could finally help pharma overcome its productivity crisis and why the payoff won’t come as quickly as the optimists claim.

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Fixing failed drugs: AI solutions for toxicity in drug discovery – part 2

21 July 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

Why do so many drug candidates fail before reaching patients – and can AI help stop the losses? In Part 2, Layla Hosseini-Gerami of Ignota Labs outlines the scope of the toxicity problem and explains why failures often come too late to fix.

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How AI and LLMs are transforming drug discovery: part 2

26 May 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

As AI reshapes scientific work, two founders debate how best to build tools scientists can trust — should we embed expertise into the model or the team? From agent-powered labs to hypothesis-generating machines, the future of drug discovery is being reimagined right now.

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How AI and LLMs are transforming drug discovery: part 1

14 May 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

AI is reshaping drug discovery – but not without resistance. In this two-part conversation, André França and Eli Pollock share honest insights about the real barriers to AI adoption in life sciences and how embedding domain expertise into AI workflows might be the key to unlocking its full potential.

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Part two: how ChatGPT enriched animal study results

15 July 2024 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

Recently there has been a flurry of announcements from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the second of a three-part series, Dr Raminderpal Singh presents an example of usage of ChatGPT, which demonstrates how accessible LLMs have become for lab scientists.

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Smarter labs, faster results: The power of automation in drug discovery

ON-DEMAND | By Drug Target Review

Manual processes are slowing down your lab. AI and automation can change that, if you know how to use them. In this free webinar, Dr Raminderpal Singh breaks down the technologies, data strategies and tools transforming early drug discovery, so you can stop guessing and start innovating.

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Part four: an industry leader’s perspective on managing data quality

24 September 2024 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers)

In this four-part series, Dr Raminderpal Singh discusses the challenges surrounding limited data quality and offers some pragmatic solutions. In this fourth article, he talks to John Conway, Chief Visioneer Officer at 20/15 Visioneers for an expert perspective.

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Beyond the hype: a veteran’s honest assessment of AI in drug discovery – Part 1

14 August 2025 | By Dr Raminderal Singh (Hitchhikers AI and 20/15 Visioneers

An interview with Thibault Géoui reveals why this technology wave might finally break through pharma's productivity crisis – and why it will take longer than the optimists claim.

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Scientific workflow for hypothesis testing in drug discovery: part 3 of 3

14 February 2025 | By Dr Raminderpal Singh (Hitchhikers AI and 20/15 Visioneers), Nina Truter

Drug discovery scientists develop and test complex hypotheses using data and expertise, and build workflows to support this. In this third and final article, Dr Raminderpal Singh and Nina Truter summarise the tools used in the scientific workflow – and include key considerations.