We're doomed we're saved #11

More than 20 years after the Human Genome Project, enabled by new sequencing technologies, researchers are making progress in exploring the vast non-coding space that constitutes 98% of our genomes. This non-coding, or "dark," DNA harbors elements with important regulatory functions in health and disease. But pinpointing disease-relevant DNA elements within this massive DNA space can be like searching for a needle in a haystack. This difficult search can be eased by artificial intelligence (AI)-based tools, which predict the context-dependent relevance of certain DNA elements and highlight their role in different diseases, from cancer to rare neurodegenerative disorders. For Episode 33 of the BioRevolution podcast, Andreas Horchler and Louise von Stechow are joined by CTO and co-founder of Berlin-based biotech LUCID Genomics, Dr. Hossein Moeinzadeh, to discuss the exciting field of non-coding DNA and how LUCID’s AI algorithm can help make sense of non-coding DNA — and how this could improve diagnoses of rare diseases and beyond. Learn more about LUCID genomics AI tool here: https://www.lucid-genomics.com/technology Find Dr. Hossein Moeinzadeh here: https://www.linkedin.com/in/mhossein-moeinzadeh/ Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: via Unsplash.

When the Swiss chemist synthesized and tested the psychedelic compound LSD in the 1930s, he knew he had found a tool to explore the human mind. Indeed, before psychedelics became illegal in the late 1960s, a mountain of evidence had been produced, showing potential benefits of psychedelic-assisted therapy for depression, anxiety, and substance abuse. After a decades-long hiatus, research on psychedelics as a treatment for psychiatric diseases is experiencing a renaissance—and initial results look promising. While the field has seen a setback with the recent request for more data by the FDA for the approval of MDMA for PTSD, research into different psychedelic compounds continues, promising new hopes to battle worldwide mental health crises. In the newest episode of the BioRevolution podcast, Andreas Horchler and Louise von Stechow discuss the history, the promise, and the risks of psychedelics as treatments for psychiatric diseases with neuroscientist, psychedelics expert, and executive coach Galyna Pidpruzhnykova https://www.linkedin.com/in/galynapidpruzhnykova/ https://www.galynapipdpruzhnykova.com/ Galyna also outlines her efforts to develop a psychedelics strategy to battle the mental health crisis in Ukraine, where the Ministry of Health published a draft law for research on psychedelic compounds just a few days after we recorded this podcast. https://www.linkedin.com/feed/update/urn:li:activity:7308180815761330176/ Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow

This time on the BioRevolution podcast: science itself. While recent surveys show persistently high trust in science worldwide, certain scientific topics have become the subject of intense societal and political debate. This politicization of science puts scientists in a difficult position when they are trying to argue based on facts. The value of facts and evidence-based science seems to be increasingly questioned by those in power and by those in control of assets. If those who make laws and regulate science don’t see evidence and consensus as reliable resources anymore, what will become of progress in biomedicine, which feeds innovation in biotech, pharma, and medicine? Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: via Photoshop AI. Further reading: https://nsf-gov-resources.nsf.gov/2023-04/EndlessFrontier75th_w.pdf https://www.nature.com/articles/s41562-024-02090-5 https://www.nature.com/articles/s41599-024-03909-2 https://www.pewresearch.org/science/2024/11/14/public-trust-in-scientists-and-views-on-their-role-in-policymaking/?utm_source=chatgpt.com https://www.nature.com/articles/d41586-025-00525-1 https://pmc.ncbi.nlm.nih.gov/articles/PMC8793038/ https://www.wissenschaftskommunikation.de/wie-lange-vertraut-man-uns-noch-83325/ https://www.nopatientleftbehind.org/defending-the-foundation-of-american-science https://theweek.com/science/distrust-science-politics-2024-public-trust-vaccines-milk-pandemic https://pmc.ncbi.nlm.nih.gov/articles/PMC11004618/ https://www.nature.com/articles/d41586-024-00238-x https://www.forbes.com/sites/innovationrx/2025/02/19/innovationrx-recursion-launches-fund-for-biotech-startups-hit-by-nih-funding-cuts/

In some respects, 2024 has been a record year for AI in biotech, with the $1 billion founding of the antibody-centered biotech company Xaira and the awarding of the Nobel Prize in Chemistry to DeepMind researchers Demis Hassabis, John Jumper, and David Baker. However, despite years of investment and innovation, we still lack an answer to the most pressing question: Will AI revolutionize drug development, or are we in a bubble that is about to burst? In episode 30 of the BioRevolution podcast, Andreas Horchler and Louise von Stechow explore various use cases for AI in biotech—from discovery to clinical development, from chemistry to biology, and from data-centric to algorithm-centric AI strategies—trying to assess where the biggest payoff will be. Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: Lucas Favre, via Unsplash. Further reading: 1. OpenAI has created an AI model for longevity science | MIT Technology Review 2. https://www.techlifesci.com/p/a-google-maps-of-human-cells 3. https://www.cas.org/resources/cas-insights/scientific-breakthroughs-2025-emerging-trends-watch#:~:text=Scientific%20breakthroughs%3A%202025%20emerging%20trends%20to%20watch%201,7%20Quantum%20computing%20getting%20practical%20...%20Weitere%20Elemente 4. Biotech Stocks Prepare For Action In 2025. Weight-Loss Drugs, AI And Trump 2.0 Are The Catalysts. | Investor's Business Daily 5. Regeneron CSO George Yancopoulos on AI’s hype and potential 6. Science in 2025: the events to watch for in the coming year 7. Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023 - PMC 8. Novo Nordisk expands AI partnership with Valo Health for development of obesity drugs | Reuters 9. Profluent Unveils OpenCRISPR-1, an AI-Designed Gene Editor 10. OpenAI has created an AI model for longevity science | MIT Technology Review 11. Clinical trial trends in 2025: Investments, wearables, and AI 12. What will be the key trends in AI innovation in the Pharmaceutical Industry in 2025? 13. Deep Genomics Introduces the Most Advanced AI Foundation Model for RNA Disease Mechanisms and Candidate Therapeutics | Deep Genomics 14. U of T researchers develop new approach using quantum computers to accelerate drug discovery | Temerty Faculty of Medicine 15. Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors | Nature Biotechnology 16. What are AI 'world models,' and why do they matter? | TechCrunch 17. Empowering biomedical discovery with AI agents: Cell 18. https://youtu.be/CWEWBgVwFc8?si=dqLn2_qGflGf19xL 19. Virtual lab powered by ‘AI scientists’ super-charges biomedical research 20. A New Kid On the Block: AI World Models In Biotech 21. 2025 AI Trends: Life Sciences Leaders on Data, Digital and AI | ZS 22. Scaling gen AI in the life sciences industry | McKinsey 23. https://www.geeksforgeeks.org/what-is-quantum-ai/ 24. Key takeaways from FDA’s draft guidance on use of AI in drug and biological life cycle | DLA Piper 25. Navigating the EU AI Act: implications for regulated digital medical products | npj Digital Medicine 26. Isomorphic Labs CEO Demis Hassabis bets on biotech’s AI future 27. De novo designed proteins neutralize lethal snake venom toxins | Nature 28. A policy framework for leveraging generative AI to address enduring challenges in clinical trials | npj Digital Medicine 29. TrialGPT: NIH algorithm uses AI to match patients to clinical trials | Association of Health Care Journalists 30. The promise and perils of synthetic data | TechCrunch 31. Profluent | Edit

2025: For millions of people, the new year starts with the self-promise to improve, to quit smoking, alcohol, to get in shape, to stay young and attractive, to basically create and become a new me. While traditionally new year vows meant to relinquish, today there seem to be many helpers in the form of biohacking. Beginning with diets and not ending with technical devices. While there are real shortcuts and fake abbreviations to reach some of those goals, there´s also traditional ways. In "New year old me – no biohacks needed", Louise von Stechow and Andreas Horchler try to distinguish what´s worth trying and what to avoid. Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: Lucas Favre, via Unsplash.

Modern humans are stressed creatures: overloaded schedules, constantly “on-call,” and social media haunting us into the late night. Part of this stress is maladaptive responses that date back to human history when stressors were about life and death and not about writing emails and making phone calls. A key player in those ancient responses is cortisol, a stress hormone that interacts with many biological functions, from heart rate to glucose metabolism, to inflammation and immune responses, as well as sleep and cognition. But is cortisol - as the social media proponents of the so-called cortisol detox make us believe - really the root of all our problems, and would it be desirable to get rid of stress altogether? Tune into episode 29 of We're Doomed, We're Saved and learn about the biological basis and myths surrounding stress and cortisol. Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: Kenny Eliason Further reading: 1. https://www.nature.com/articles/s41380-021-01224-9 2. https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1085950/full 3. https://www.mdpi.com/2073-4409/12/23/2726 4. https://pubmed.ncbi.nlm.nih.gov/34290370/ 5. https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2018.00127/full 6. https://www.nature.com/articles/s44220-023-00016-0 7. https://www.geo.de/wissen/gesundheit/cortisol-reduzieren--was-steckt-hinter-dem-gesundheitstrend--34986216.html

Science can be complex and difficult to grasp, yet public understanding is crucial for navigating issues like disease risk, climate change, and pandemics. Clear, engaging science communication can help prevent misinformation and conspiracy theories, offering facts in place of myths. But how can we make science more digestible and appealing? Counterintuitively, it might be less facts and more emotions that can help to make science more appealing, more impactful – both when communicating to the public and to fellow scientists. In episode 28 of We’re doomed, We’re saved, Andreas Horchler and Louise von Stechow discuss strategies for scientific storytelling, drawing on principles that go back to ancient Greece and draw from modern brain science. Spoiler: It´s not as hard as it may look. Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: bernard-hermant-qTpc0Vj4YoE-unsplash via Unsplash Further reading: Cron, Lisa: "Wired for story, The Writer's Guide to Using Brain Science to Hook Readers from the Very First Sentence" Clarkson Potter/Ten Speed, 2012 Gallo, Carmine: "Talk like Ted" Main Market Edition, 2022

In the expensive and failure-prone process of drug development, artificial intelligence (AI) can serve both as an efficiency tool and as a creativity tool. Increased efficiency means shorter timelines, reduced investment, and earlier insights into success or failure. This can lead to more opportunities to bring new drugs to patients. Increased creativity means exploring new areas in drug discovery and development, such as identifying new patterns in targets, drug molecules, and patient populations that may be unintelligible to the human eye. While we are witnessing the first tangible milestones of AI in drug development, the hype in the field can lead to inflated expectations of its benefits. To assess the true potential of the technology, we must also recognize its challenges, such as the algorithms' "black box" nature, their propensity for hallucination, and data bias. Only by being transparent about both the potential and the limitations of AI can we increase the trust of drug developers—and most importantly, our customers: patients. Listen to episode 27 of We’re Doomed, We’re Saved to learn more about the potential of AI for pharma and biotech. Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: ej-strat-VjWi56AWQ9k-unsplashvia Unsplash References: 1. https://www.nature.com/articles/s41591-023-02361-0 2. https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/ 3. https://www.nature.com/articles/d41586-023-02896-9 4. https://www.nature.com/articles/d43747-024-00084-w 5. https://www.nature.com/articles/d43747-024-00084-w 6. https://www.nature.com/articles/d43747-024-00084-w 7. https://endpts.com/the-endpoints-slack-interview-siddhartha-mukherjee-on-the-doctor-writer-worldview-ai-and-the-future-of-cancer/ 8. https://endpts.com/the-endpoints-slack-interview-siddhartha-mukherjee-on-the-doctor-writer-worldview-ai-and-the-future-of-cancer/ 9. https://hbr.org/2024/05/ais-trust-problem

How will the medicine of the future look? Healthcare and medicine are on the verge of transformative change, driven by new technologies such as artificial intelligence, telemedicine, and wearable devices. Alongside the technologization and virtualization of medicine, there is a shift from reactive "fix the broken" approaches to preventative strategies and from one-size-fits-all treatments to personalized medicine. In this future, human healthcare professionals and machines will work hand-in-hand to deliver the best possible care, with empowered patients acting as equal decision-makers who understand and access their own healthcare data. However, a darker scenario could see medicine becoming fully industrialized and dehumanized. In episode 26 of We’re Doomed, We’re Saved, Andreas Horchler and Louise von Stechow outline the key trends shaping the future of medicine and discuss the opportunities and risks that accompany these developments. Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: alexander-sinn-KgLtFCgfC28-unsplash via Unsplash References: https://www.nature.com/articles/s41591-019-0693-y?fbclid=IwZXh0bgNhZW0CMTAAAR0RAb4UU5v5896AQfVNYfdCpLi80iN7JwoZux55ffxyI9W7TMsqVPakS3M_aem_49GYkWynL_l8fmMWXq_Xlg https://www.zukunftsinstitut.de/zukunftsthemen/megatrend-gesundheit https://www.nature.com/articles/s41591-024-03097-1#Sec9 https://www.nature.com/articles/s41591-023-02700-1 https://ai.nejm.org/doi/full/10.1056/AIcs2300145 https://www.nature.com/articles/s41599-022-01451-7 https://www.nejm.org/doi/10.1056/NEJMra2215899?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed https://www.imperial.ac.uk/news/167866/information-handling-some-health-apps-secure/ https://journals.sagepub.com/doi/full/10.1177/1357633X211022907 https://www.mckinsey.com/industries/life-sciences/our-insights/germanys-e-health-infrastructure-strengthens-but-digital-uptake-is-lagging https://www.mckinsey.com/industries/life-sciences/our-insights/german-e-health-offerings-expand-but-adoption-remains-uneven https://empeek.com/insights/everything-about-telemedicine-statistics-usage-trends/ https://blogs.deloitte.co.uk/health/2023/11/the-future-of-health-in-europe-digital-equitable-sustainable.html https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-shaping-the-future-of-european-healthcare.pdf https://www.nature.com/articles/s41569-021-00522-7 https://web-assets.bcg.com/1e/74/5d14d48346bcb56a79c6e7e7ba0f/bcg-the-future-of-digital-health-2024-jan-2024-1.pdf

Some 36 months after the release of ChatGPT, the verdict is still out on the role that large language models (LLMs) will play in biotech, pharma, and medicine. On paper, the range of tasks that LLMs can perform in biomedical research and healthcare is vast—excavating relevant information for drug discovery from mountains of scientific literature, designing novel proteins, transcribing doctors' notes, aiding diagnostic decision-making, and acting as patient-facing chatbots. But given the models’ propensity to hallucinate, we need to define how much error we can tolerate for different LLM use cases in the biomedical fields and create evaluation frameworks that allow us to apply the models confidently. In some cases, it might turn out that the time spent for human supervision of the model will outweigh the efficiency gain. In episode 25 of We’re doomed we’re saved we talk to idalab founder and mathematician, Paul von Bünau we discuss the promise and challenges of LLMs in the biomedical field and ask the question if we can ever stop them from hallucinating. Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: jo-coenen-studio-dries-2-6-yST9mzlMVLQ via Unsplash References: Excavating scientific literature 1. https://www.nature.com/articles/s41587-023-01788-7 2. https://idalab.de/insights/how-large-language-models-excavate-crucial-information-to-scale-drug-discovery 3. https://www.cell.com/molecular-therapy-family/nucleic-acids/fulltext/S2162-2531(23)00222-6#secsectitle0015 Unburdening Healthcare 1. https://www.nature.com/articles/s41591-023-02700-1 2. https://medium.com/mantisnlp/applications-of-llms-in-patient-care-83e07548dbb1#:~:text=Applications%20of%20LLMs%20in%20Patient%20Care%201%201.,6%206.%20Personalized%20Health%20Plans%20and%20Coaching%20 3. https://www.nature.com/articles/s41591-023-02700-1 4. https://arxiv.org/pdf/2303.16416 5. https://www.nature.com/articles/s41467-024-46411-8 6. https://link.springer.com/article/10.1007/s00330-023-10213-1 7. https://link.springer.com/article/10.1007/s00330-023-10213-1 8. https://link.springer.com/article/10.1007/s00330-023-10213-1 9. https://www.nature.com/articles/s41591-024-03097-1#Sec9 Reading molecular language 1. https://academic.oup.com/bioinformatics/article/36/4/1234/5566506 2. https://arxiv.org/abs/2106.03598 3. https://resources.nvidia.com/en-us-hc-biopharma/hc-solution-overview-5 4. https://www.nature.com/articles/s41592-024-02201-0#author-information 5. https://www.prnewswire.com/news-releases/ginkgo-bioworks-and-google-cloud-partner-to-build-next-generation-ai-platform-for-biological-engineering-and-biosecurity-301912283.html 6. https://www.nature.com/articles/s41598-024-61124-0 7. https://www.nature.com/articles/s41587-022-01618-2 8. https://www.biopharmatrend.com/post/835-14-companies-pioneering-ai-foundation-models-in-pharma-and-biotech/ 9. https://www.biorxiv.org/content/10.1101/2023.01.11.523679v1 10. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-024-05847-x 11. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-024-05847-x 12. https://arxiv.org/abs/2403.04197 13. https://arxiv.org/abs/2311.07621