Venki breaks his thoughts down into two categories, the first of which is around general integrity in research. Measures of robust research include whether published research is sufficiently detailed that someone could perform the experiment and observe results that reproduce the reported research outcomes. This is just one measure to help determine the quality of research being conducted and is a core tenet of peer review, by peers and competitors who would be able to expose any issues in the research. There is also the conscious or unconscious cherry-picking of observations, which can again be mitigated through community consensus and conversation. If something is proven to be wrong, this consensus can be challenged and eventually help shift our understanding of the problem.

However, Venki also discusses the much bigger and more pervasive issue of misinformation, which goes beyond the scientific community and impacts all aspects of our lives, including politics, behaviour, economics, and more. Many threads of life are susceptible to the negative impacts of misinformation, which is being accelerated further by the ease at which information can be shared, and the contribution that AI is making to the volume of misinformation available in the wild.

Venki encourages us to be alert and involved as a society in combatting misinformation through robust critical thinking, to help prevent the spread of incorrect information that could otherwise go on to misinform policy and processes that impact us every day.

Subscribe now to be notified of each weekly release of the latest TL;DR Short, and catch up with the entire series here. 

If you’d like to suggest future contributors for our series or suggest some topics you’d like us to cover, drop Suze a message on one of our social media channels and use the hashtag #TLDRShorts.

The post TL;DR Shorts: Professor Venki Ramakrishnan on Trust in Research appeared first on Digital Science.

In our first Speaker Series chat of 2025, and in a month that heralds much political interest in the role of truth and trust in society, Deborah delves into the challenges and opportunities facing science communication today. She explores the importance of storytelling, the necessity of improving scientific literacy in all, and the steps needed to build a future where science journalism drives meaningful dialogue and action. Her insights offer a vision of how journalists and scientists can work together to showcase the human side of science and ensure it serves all communities fairly and effectively.

Deborah Blum is an acclaimed science journalist, Pulitzer Prize-winning author, and Director of the Knight Science Journalism program at MIT. With a career spanning decades, she has worked tirelessly to bridge the gap between science and the public through her compelling storytelling and her commitment to advancing science literacy. Her influential books, which include The Poisoner’s Handbook and The Poison Squad, explore the intersection of science, history, and societal impact. At the Knight Science Journalism program, Deborah leads efforts to train and support journalists worldwide, fostering a global community dedicated to improving the quality of science communication and addressing pressing challenges like misinformation and declining public trust in science.

The Role of Science Journalism

Science journalism plays an important role in making connections between scientific discoveries and people’s everyday lives. Deborah describes the role that science journalists play in helping to translate complex scientific ideas into stories that resonate with readers. Good storytelling can make even the most abstract research feel relevant and engaging.

In a world increasingly driven by scientific and technological progress, this connection is more important than ever. Deborah highlights that science journalism not only informs but also inspires public interest and action. By showing how science impacts issues like health, climate change, and technology, journalists help communities see the relevance of research in shaping our future. As she puts it, “We need to write about science and its impacts, right? We need to acknowledge that it has these social and cultural impacts. We need to illuminate those in all of their social justice issues.”

The Impact of the KSJ Program

At the heart of Deborah’s work is her leadership of the Knight Science Journalism (KSJ) program at MIT, where she has been Director for a decade, a role which she will be stepping down from in July 2025. The KSJ program is somewhat of a global engine for excellence in science communication. The program provides resources, fellowships, and a thriving community for journalists to deepen their expertise and broaden their perspectives.

But the KSJ program goes beyond training – it builds a community of professionals who share a commitment to thoughtful, accurate reporting. Deborah believes this community approach is critical in a world where misinformation spreads rapidly. When journalists feel supported and connected, they are better equipped to tackle tough stories and elevate public understanding. This global impact is reflected in the program’s alumni, who are shaping conversations about science across continents.

Challenges in Science Communication

Communicating science effectively isn’t without its hurdles. Deborah points out that misinformation is casting an ever-growing shadow, compounded by public scepticism and limited access to scientific education and critical thinking skills. We now live in an age where everyone has a platform from which they can share their thoughts, but not everyone values the accuracy of those thoughts. Deborah emphasised the need for journalists to cut through the noise with credible, engaging stories.

Another challenge is the disconnect between scientists and the public. Deborah argues that many researchers struggle to communicate their work in accessible ways, leaving gaps that can be filled by misunderstanding or fear. “The more people can see scientists as actual human beings next door, the better off we all are,” she insists. Building bridges between these groups is crucial to fostering a more informed and engaged society.

The Importance of Science Literacy

Science literacy is the foundation of informed decision-making, yet many people lack the tools to critically evaluate scientific information, with many people even being fearful and actively disengaged with science. Deborah shares her thoughts about the shortcomings of educational systems. She believes that by not teaching people how to think critically about science, we are doing a disservice to society. Without this foundation, the public is more vulnerable to the potentially negative consequences of pseudoscience and misinformation.

Deborah believes that improving science literacy requires a collective effort. Journalists, educators, and policymakers must work together to ensure that everyone has access to clear and reliable information. It is not only about teaching facts but also about teaching people how to think, and how to evaluate those facts for any inherent bias. “We don’t want everyone to be a scientist, but we do want everyone to know something about science and how to make decisions about science and to recognize that every time you fry an egg or make a cup of tea or peel a banana, you’re engaging with chemistry, right, in everyday science. And it makes the world that much more interesting.” By developing people’s ability to understand and question scientific claims, society can make better choices for the future, and hold bad actors accountable for bad science.

Building Trust in Science

Trust in science has been eroded in recent years, but Deborah sees this as an opportunity for change. Trust isn’t automatically granted – it is something that must be earned. Scientists and journalists both have roles to play in this process. Deborah encourages researchers to embrace transparency and share not just their successes but also their uncertainties and failures, to humanise their motivations and actions, and to showcase the more realistic side of the scientific process.

She also highlights the importance of equity in building trust. Science needs to serve all communities, not just a select few, so addressing social justice issues in science such as unequal access to education and healthcare can help rebuild trust in science’s potential to improve lives. Through honest and inclusive communication, science can regain its role as a trusted guide for society.

The Future of Science Journalism

Looking ahead, Deborah envisions a future where science journalism is more valuable than ever. She sees the next generation of journalists as not only storytellers but also advocates for social justice. She believes that the future of science journalism lies in showcasing the human side of science, and how it impacts people and communities.

Deborah encourages young journalists to be fearless in tackling big issues, from climate change to misinformation. We need journalists who are smarter, braver, and more curious. By embracing innovation and collaboration, science journalism can continue to be a powerful force for good, shaping public understanding and inspiring meaningful action in an increasingly complex world.

Deborah’s thoughts are a powerful reminder of the critical role that science journalism plays in shaping a better-informed, more engaged society. From her leadership of the Knight Science Journalism program to her advocacy for transparency, equity, and science literacy, Deborah tangibly demonstrates how storytelling can drive meaningful change. As we face global challenges like misinformation, climate change, and declining trust in science, her call for collaboration and innovation in both journalism and science communication is more relevant than ever. By fostering a new generation of journalists who are fearless, thoughtful, and socially conscious, Deborah is helping to build a future where science journalism not only informs but also empowers us to build a better world.

You can watch the full interview with Deborah on our YouTube channel, and check out our Speaker Series playlist on YouTube which includes chats with some of our previous speakers, as well as our TL;DR Shorts playlist with short, snappy insights from a range of experts on the topics that matter to the research community. We’ve even joined the podcast universe! Catch our 2025 Speaker Series season and our chat with Deborah on Spotify or Apple Podcasts.

With thanks to Huw James from Science Story Lab for filming and co-producing this interview. Filmed at the Knight Science Journalism offices at MIT in Cambridge, Massachusetts, USA in April 2024.

The post Science Journalism and Social Justice – meet Deborah Blum appeared first on Digital Science.

Every Muppets fan knows that Christmas is all about being revisited by people you’ve previously encountered. So from 25th December to 5th January we’ll be sharing our 12 Days of DSmas. Check back daily as we share a Speaker Series chat each and every day. Happy Holidays from the Digital Science Thought Leadership Team!

Merry Dr Chris Van Tulleken-mas! We chatted with Chris online about research integrity, impact, openness, and investigative research. Catch his interview here, and don’t forget to watch his Xmas Lectures on BBC for The Royal Institution this year!

Chris on Spotify

Chris on Apple Podcasts

Chris on YouTube

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Professor Dame Athene Donald joined our Speaker Series line-up in February after her Speaker Series Live talk at the Ri in London, UK. Here she is talking about why we need to empower women in STEM from the ground up.

Athene on Spotify

Athene on Apple Podcasts

Athene on YouTube

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It’s time to go to Berlin, Germany and catch Matyas Kovacs at the Falling Walls Summit. Matyas shared his thoughts on communication and innovation to impact all of society with science.

Matyas on Spotify

Matyas on Apple Podcasts

Matyas on YouTube

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As a Nobel laureate and former president of The Royal Society, Professor Venki Ramakrishnan has long played a role in shaping a more innovative, inclusive and impactful research culture, which we chatted about during his live Speaker Series lecture at the Ri. We went to Cambridge, UK to hear his thoughts on curiosity, competition and collaboration.

Venki on Spotify

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Venki on YouTube

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As Chief Publishing Officer at PLOS, Niamh provides business leadership for the entire PLOS portfolio to advance PLOS’s vision and mission. In this episode Niamh talks about the evolving landscape of scientific research and the push towards open science, including her journey from the early days of advocating for public access to research, to tackling current challenges like making science more inclusive and accessible.

Niamh on Spotify

Niamh on Apple Podcasts

Niamh on YouTube

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Building communities is hard, but Alice Meadows has worked hard to make it look effortless. Here she is in Boston, MA, USA, telling us about the power of persistent identifiers.

Alice on Spotify

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Alice on YouTube

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It’s New Year’s Eve, and a time to reflect on the past and make plans for the months ahead. When we visited the Max Planck Institute in Berlin, Germany, we added to the echoes of amazing research conversations resonating around their iconic library when we chatted about the history, philosophy and future of research with Dr Maria Avxentevskaya and Dr Ben Johnson.

Maria and Ben on Spotify

Maria and Ben on Apple Podcasts

Maria and Ben on YouTube

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Happy New Year! We caught up with pro-skater Rodney Mullen at his home in Los Angeles, USA to hear his thoughts on why we need diverse minds to innovate in all walks – and ollies – of life. And, since it’s the new year and you’re probably feeling a little “sleep deprived”, you can also follow this up with his live Speaker Series lecture at the Ri.

Rodney on Spotify

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Rodney on YouTube

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If you’ve been eating as much cheese as this author, dearest gentle reader, you too will be experiencing a fascinatingly slippery grasp on reality – which brings us to Day 9’s featured speaker. “Is Maths Real?” was the question that Dr Eugenia Cheng posed in her live Speaker Series lecture at the Ri. I caught up with her ahead of her lecture in the iconic Faraday lecture theatre in London, UK to talk about why we need to break down barriers of knowledge in research, and reunite STEM and the humanities for impactful change.

Eugenia on Spotify

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Dr Gilbert De Gregorio leads the Frontiers Planet Prize. I caught up with him in Berlin, Germany, to talk about why we need more inclusive competitions to catalyse innovation that impacts our global society.

Gilbert on Spotify

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Gilbert on YouTube

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2024 was a wild ride for global politics, and research is not immune to its changes. I caught up with Professor Jenny Reardon in Cambridge, UK, to learn more about how we can work with politics, and not against it, to provide solutions for everyone across the world, and where red tape remains to be overcome.

Jenny on Spotify

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Jenny on YouTube

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Our final Speaker Series guest of 2024 was Dr Danny Hillis. We visited the Applied Invention offices in Cambridge, MA, USA, where innovator, inventor, and Imagineer Danny shared his thoughts on how we can use novel technology to combat novel challenges in mis- and disinformation and make the most meaningful impact from data.

Danny on Spotify

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Danny on YouTube

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The post The 12 Days of DSmas appeared first on Digital Science.

Subscribe now to be notified of each weekly release of the latest TL;DR Short, and catch up with the entire series here. 

If you’d like to suggest future contributors for our series or suggest some topics you’d like us to cover, drop Suze a message on one of our social media channels and use the hashtag #TLDRShorts.

The post TL;DR Shorts: Venki Ramakrishnan on the Future of Biology appeared first on Digital Science.

Danny uses agriculture as one example of an area of research vital to the survival of humanity where we aren’t doing enough research. Any fellow BBC Countryfile fan will know that farmers work incredibly hard tending to their agricultural land and responding to the dynamic needs placed on them by the changing climate and other factors. Though they may like to, they often don’t have time to do experiments and contribute to the corpus of research information in this space in a way they would like to.

However, if we start to collect data from the automation of the mechanisation farmers used to work the land, we can allow these “robots” to conduct a series of experiments that humans don’t have the time to do.

Danny believes that in the future these machines will also contribute to planning future experiments to explore such research spaces. He believes that the future of automated science will be done by AI – allowing humans to increase the number of experiments they can conduct, increase the amount of data gathered, and increase the number of hypotheses being tested.

Subscribe now to be notified of each weekly release of the latest TL;DR Short, and catch up with the entire series here. 

If you’d like to suggest future contributors for our series or suggest some topics you’d like us to cover, drop Suze a message on one of our social media channels and use the hashtag #TLDRShorts.

The post TL;DR Shorts: Dr Danny Hillis on the Automated Future of Research appeared first on Digital Science.

As part of our ongoing investigation into Research Transformation, we are delighted to present a new report, Research Transformation: Change in the era of AI, open and impact.

Within the report, we sought to understand from our academic research community how research transformation is experienced across different roles and responsibilities. The report, which is a mixture of surveys and interviews across libraries, research offices, leadership and faculty, reflects transformations in the way we collaborate, assess, communicate, and conduct research.

The positions that we hold towards these areas are not the same as those we held a decade or even five years ago. Each of these perspectives represent shifts in the way that we perceive ourselves and the roles that we play in the community. Although there is concern about the impact that AI will have on our community, our ability to adapt and change is reflected strongly across all areas of research, including open access, metrics collaboration and research security. That such a diverse community is able to continually adapt to change reflects well on our ability to respond to future challenges.

Key findings from the report:

• Open research is transforming research, but barriers remain

• Research metrics are evolving to emphasize holistic impact and inclusivity

• AI’s transformative potential is huge, but bureaucracy and skill gaps threaten progress

• Collaboration is booming, but increasing concerns over funding and security

• Security and risk management need a strategic and cultural overhaul

We do these kinds of surveys to understand where the research community is moving and how we can tweak and adapt our approach as a company. We were very grateful to the great minds who helped us out with a deep dive into what has affected their roles and will affect their roles going forward. Metrics, Open Research and AI are very aligned with the tools that we provide for academics, and the strategy we have to make research more inclusive, transparent and trustworthy.

The post Presenting: Research Transformation: Change in the era of AI, open and impact appeared first on Digital Science.

Open research is transforming the way research findings are discovered, shared and reproduced. As part of our commitment to the Open Principles and research transformation, we are looking into how open research is transforming roles, approaches, policies and, most importantly, mindsets for everyone across the research landscape. See our inspiring transformational stories so far.

Academia is at a pivotal juncture. It has often been criticized as slow to change, but external pressures from an increasingly complex world are forcing rapid change in the sector. To understand more about how the research world is transforming, what’s influencing change, and how roles are impacted, we reached out to the research community through a global survey and in-depth interviews.

Research Transformation stories so far…

Digital Science Open Principles

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Open Access: Mo Money Mo Problems

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The Initial Transformation

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Academic Survey Report Pre-registration

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State of Open Data 2024 – Special Edition

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Will 2025 be a turning point for Open Access? – Digital Science

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How has innovation shaped Open Research? What does the future hold – especially with the impact of AI? Here’s Dan Valen speaking about Figshare’s key role, with innovation helping to transform the research landscape.

Digital Science has always understood its role as a community partner – working towards open research together. Here’s some ways in which we have helped to transform research over the last 14 years.

In our first piece, Simon Porter and Mark Hahnel introduce the topic and detail the three areas the campaign will focus on.

The Story of Data Transformation

The Story of Connection

The Story of Research Innovation

• Making data more usable
• Opening up channels & the flow of information
• Transforming data through innovation & AI
• Maintaining trust & integrity

• Seeing both perspectives
• What success looks like for knowledge transfer
• Evolving roles and the role of people in bridging gaps

• Research Transformation White Paper
• How have roles changed:
  • In Academia?
  • In Publishing?
  • In Industry?
• State of AI Report
• How are we using AI in our research workflows?

Research Transformation

The way we interact with information can amplify our ability to make connections, and in doing so transforms how we understand the world. Supercharged by the AI moment that we are in, the steady march of digital transformation in society over the last three decades is primed for rapid evolution. What is true for society, is also doubly so for research. Alongside ground-breaking research and discoveries is the constant invitation to adapt to new knowledge and abilities. Combine the general imperative within the research sector to innovate with the rapidly evolving capabilities of generative AI and it is safe to say that expectations are high. Taking effective advantage of new possibilities as they arise however, requires successful coordination within society and systems. 

There is an art to transformation, and understanding the mechanisms of transformation places us in the best position to take advantage of the opportunities ahead.

In this series, we specifically seek to explore Research Transformation with an eye to adapting what we already know to the present AI moment. Transformation in Research is not just about digital systems, but it is also about people and organisations – crossing boundaries from research to industry, emerging new research sectors, creating new narratives and adapting to the possibilities that change brings.

At Digital Science, we have always sought to be an integral part of research transformation, aiming to provide products that enable the research sector to evolve research practice – from collaboration and discovery through to analytics and administration. Our ability to serve clients from research institutions to funders, publishers, and industry has placed us in a unique position to facilitate change across the sector, not simply within silos, but between them. In this series, we will be drawing on our own experiences of research transformation, as well as inviting perspectives from the broader community. As we proceed we hope to show that Research Transformation isn’t just about careful planning, but requires a sense of playfulness – a willingness to explore new technology, a commitment to a broader vision for better research, as well as an ability to build new bridges between communities.

In the first of three themes, we will cover Research Transformation from the perspective of the data and metadata of research. How do changes to the metadata of research transform our ability to make impact, as well as see the research community through new lenses? How does technology enable these changes to occur? Starting almost from the beginning, we will look at how transitions in publishing practice have enabled the diversity of the research workforce to become visible. We will also trace the evolving story of the structure of a researcher’s papers, from the critical use of identifiers, to adoption of the credit ontology, through to the use of trust markers (including ethics statements and data and code availability, and conflict of interest statements.) The evolving consensus on structured and semi structured nature of research articles changes not only the way we discover, read and trust individual research papers, but also transforms our ability to measure and manage research itself.

Our focus will not only be reflective, but will also look forward to the emerging challenges and opportunities that generative AI offers. We will ask deep questions about how research should make its way into large language models. We also explore the new field of Forensic Scientometrics that has arisen in response to the dramatic increase in bad faith science in part enabled by generative AI, and the new research administration collaborations that this implies – both with research institutions and across publishing. We will aso offer more playful, experimental investigations.  For example, a series on ‘prompt engineering for librarians’ draws on the original pioneering spirit of the 1970’s MEDLARS Analysts to explore the possibilities that tools such as OpenAI can offer. 

Lifting up from the data, we note that a critical part of our experience of research transformation has been the ability to experience and connect with research fromshifting perspectives. In this second theme exploring research transformation, we aim to celebrate the art of making connections, from the personal transformations required  to make the shift from working within research institutions to industry, through to the art of building research platforms that support multiple sectors. We also cover familiar topics from new angles, For instance, how do the FAIR data principles benefit the pharmaceutical industry? How do we build effective research collaborations with emerging research sectors in Africa?

In our third theme, we will explore Research Transformation from the perspective of innovation, and how it has influenced the way research is conducted. Culminating in a  Research Transformation White Paper we will explore how roles have changed in academia, publishing, and industry.  Within this broader context of Research transformation, we ask ‘How are we using AI in our research workflows?’ How do we think we will be using AI in years to come?

Of course, many of us in the Digital Science community have been engaging with different aspects of research transformation over many years. If you are keen to explore our thinking to date, one place that you might like to start is at our Research Transformation collection on Figshare. Here we have collated what we think are some of our most impactful contributions to Research Transformation so far. We are very much looking forward to reflecting on research transformation throughout the year. If you are interested in contributing, or just generally finding out more, why not get in touch?

The post Welcome to… Research Transformation!  appeared first on Digital Science.

A ‘Nobel’ Purpose

Alfred Nobel established the Nobel Prizes in the late 19th century to honour individuals or organisations that make extraordinary contributions in fields including chemistry, physics, medicine, economics, literature, and peace. The goal was to reward those who advance knowledge, promote human welfare, or contribute to peace. While his vision was inclusive, the early years of the prize often reflected the male-dominated world of science and academia.

The Impact of Winning Awards

Winning a prestigious award like the Nobel Prize can transform a career. It brings visibility, funding, and opportunities, enhancing credibility and often leading to leadership positions or influence in policy-making. However, with the honour comes pressure – the recognition can be empowering but may also come with additional scrutiny and challenges, making it a double-edged sword.

Gender Imbalance in Science Awards

All the winners of the 2024 science Nobel Prizes are men, especially at a time when more women are entering STEM fields and making significant contributions. This imbalance raises concerns about whether institutional barriers or unconscious biases continue to prevent deserving women from receiving recognition. The lack of diversity not only limits the acknowledgment of talent but also risks sending a discouraging message to future generations of women in science.

Why Diversity in Awards Matters

Diversity in awards is critical because it ensures that people from all backgrounds are seen and celebrated. When prize committees recognise a wide range of contributors, it helps break stereotypes and demonstrates that success in science and other fields is not limited by gender or background. It also pushes institutions to create a more inclusive environment, giving everyone a fair shot at success and setting the tone for a more diverse future in STEM fields.

The Frontiers Planet Prize: A Step Towards More Inclusive Recognition

A positive example of how awards are moving towards greater inclusivity is the Frontiers Planet Prize. This prize recognizes groundbreaking research addressing urgent global challenges like climate change and sustainability. The organisers have made a deliberate effort to highlight the work of a diverse group of researchers, shifting towards a more inclusive vision of scientific achievement. By focusing on issues that affect society as a whole, the prize aims to recognize a broader range of contributions, creating a model for how other awards can diversify and better reflect the world we live in.

You can watch the full interview with Gilbert on our YouTube channel, and check out our Speaker Series playlist on YouTube which includes chats with some of our previous speakers, as well as our TL;DR Shorts playlist with short, snappy insights from a range of experts on the topics that matter to the research community.

With thanks to Huw James from Science Story Lab for filming and co-producing this interview.

The post Incentives for Innovation – meet Dr Gilbert De Gregorio appeared first on Digital Science.

Dr Cave is co-founder and Chief Scientific Officer of Twelve, a chemical technology company that is working on converting excess carbon dioxide into useful materials such as sustainable fuels and plastics. We recorded her thoughts at last year’s Science Foo Camp, or Sci Foo – an unconference that brings together people from numerous different backgrounds, levels and types of experience to see which hot topics and future collaborations arise.

Given the Sci Foo setting, it was perhaps no surprise that when Etosha was asked about what the future of research might look like, she talked about collaboration and groups of diverse make-up working together to solve problems. She hopes that in the future we can benefit from the creation of more innovation playgrounds to catalyse creative thinking for big teams of diverse minds that are focused on solving a specific problem. This space for creativity is certainly an ethos that Etosha applies to her and her teams’ work at Twelve.

Subscribe now to be notified of each weekly release of the latest TL;DR Short, and catch up with the entire series here. 

If you’d like to suggest future contributors for our series or suggest some topics you’d like us to cover, drop Suze a message on one of our social media channels and use the hashtag #TLDRShorts.

The post TL;DR Shorts: Dr Etosha Cave on a Collaborative Future for Research appeared first on Digital Science.

Drug discovery has come a long way. It started with natural remedies and saw landmark serendipitous discoveries like penicillin in 1928. The mid-20th century introduced rational drug design, targeting specific biological mechanisms. Advances in genomics, high-throughput screening, and computational methods have further accelerated drug development, transforming modern medicine. However, despite these advances, fewer than 10% of drug candidates succeed in clinical trials (Thomas, D. et al. Clinical Development Success Rates and Contributing Factors 2011–2020 (BIO, QLS & Informa, 2021)). Challenges like pharmacokinetics and the complexity of diseases hamper progress. While we no longer fear smallpox or polio and have effective treatments for bacterial infections and Hepatitis C, today’s most damaging diseases are complex and hard to treat due to our limited understanding of their mechanisms.

Nature 627, S2-S5 (2024) https://doi.org/10.1038/d41586-024-00753-x

Cue paradigm shift. DeepMind’s AlphaFold has revolutionized biology by accurately predicting protein structures, a task crucial for understanding biological functions and disease mechanisms. The economic prowess of Deepmind is also creating some mind-blowing figures. The estimated replacement cost of current Protein Data Bank archival contents (the dataset from which the AlphaFold models were built) exceeds US$20 billion (assuming an average cost of US$100,000 for regenerating each of the >200,000 experimental structures). AlphaFold has subsequently generated a database of more than 200 million structures. Some back of the envelope maths infers that this would have cost us $20,000,000,000,000 using the original methods.

Number of protein structures in Alphafold. Credit: Deepmind

Of course, there are many simultaneous attempts to move the research needle using AI. A team from AI pharma startup Insilico Medicine, working with researchers at the University of Toronto, took 21 days to create 30,000 designs for molecules that target a protein linked with fibrosis (tissue scarring). They synthesized six of these molecules in the lab and then tested two in cells; the most promising one was tested in mice. The researchers concluded it was potent against the protein and showed “drug-like” qualities. All in all, the process took just 46 days. Scottish spinout Exscientia has developed a clinical pipeline for AI-designed drug candidates.

Not only does the platform generate highly optimized molecules that meet the multiple pharmacology criteria required to enter a compound into a clinical trial, it achieves it in revolutionary timescales, cutting the industry average timeline from 4.5 years to just 12 to 15 months. These companies have the technical know-how to build the models, and most likely some internal data with which to train them on. But they need more.

The Power of Existing Data

Platforms like the Dimensions Knowledge Graph, powered by metaphactory, demonstrate the potential of structured data. With over 32 billion statements, it delivers insights derived from global research and public datasets. Connecting internal knowledge with such vast external data provides a trustworthy, explainable layer for AI algorithms, enhancing their application across the pharma value chain.

Knowledge democratization bridges the gaps in the pharma value chain. Credit: metaphacts

AI is not all there is to be excited about in drug discovery. A further technological, serendipitous paradigm shift could amplify the results of AI alone. Once trained, machine-learning models can be updated as and when more data become available. With ‘federated learning’, separate parties update a shared model using data sets without sharing the underlying data. Advances in federated learning allow for collaborating across organizations without sharing sensitive data, maintaining privacy while pooling diverse datasets. Federated learning is a machine learning technique that allows models to be trained across multiple companies holding local data samples. Instead of sending data to a central server, each device sends its model updates (e.g., weight changes) to the central server. This allows further reduction in time and cost in the drug discovery process by improving predictive models, without leaking private company held datasets. Public data can augment local datasets held in corporate R&D departments, enriching the training process. Public data with similar characteristics can help in creating more comprehensive models. This is why we need more, better described open academic research data.

Pharmaceutical companies of the world should be engaging further with both open academic data aggregators in order to assist in the improvement of metadata quality and highly curated linked datasets like the ones supported by the Dimensions Knowledge Graph and metaphactory. The limiting factor is not the AI capabilities, it is the amount of high-quality, well described data that they can incorporate into their models. They need to:

1. Acquire: Gather data from diverse sources, including internal external datasets. Make use of federated learning.
2. Enhance: Enrich data with metadata and standardized formats to improve utility and interoperability.
3. Analyse: Use new models to establish patterns, trends and drug candidates.

You may be thinking that this isn’t a serendipitous leap. This is the fruition of decades of research moving us to a point where these technologies can be applied. You may be right. Either way, the timing of these paradigm changing tools does feel serendipitous. Without AI and federated learning, we could not tackle today’s complex diseases in such an efficient manner. There is a long way to go, but by continuing to curate and build on top of academic data, we can push the boundaries of what’s possible in modern medicine.

This is part of a Digital Science series on research transformation. Learn about how we’re tracking transformation here.

The post The next serendipitous paradigm shift for drug discovery appeared first on Digital Science.