The Biotech Futurist

Half of the recent intensive-care stays in the most used public ICU database have no infusion rows at all, so part of the drift that people train models to chase belongs to the recording system. A cardiology group reports that the information in circulating troponin sits in which compartment carries it. A four-metabolite urine panel separated eight cancers well, and its authors did the screening arithmetic themselves and landed on a positive predictive value of 6.7%. Earth observation published a year-long single-blind test against metered gas releases, in which artificial-intelligence methods produced most of the false positives. Three intensive-care trials appeared in one journal on the same day, and the number that triggers treatment escalation in all of them is a weighted sum whose weights its own authors describe as arbitrary.Sources: https://lucafusarbassini.org/d/2026-10-15

Some antisense oligonucleotides kill prion-infected mice and leave healthy mice unharmed, so the standard preclinical safety test cannot see this toxicity at all. The same shape of problem recurred all day. A nine-valent Escherichia coli vaccine raised strong antibodies in 17,701 older adults and protected nobody. A trauma biomarker read for years as endothelial turns out to sit in epithelium. A national census of Tanzanian laboratories found 13% of installed analysers not working, breakdown first among the causes. Each number was fine; its meaning came from somewhere nobody had checked.Sources: https://lucafusarbassini.org/d/2026-10-14

Two papers today trace the two most useful DNA machines in biology back to the same conflict, bacteria against their viruses. One is a bacterial reverse transcriptase that adds repeats the way telomerase does. The other, proposed as the ancestor of CRISPR, is a phage protein that reads double-stranded DNA with a code skipping every third base. Both carry the same three-part design: an enzyme, a noncoding RNA built of tandem repeats, and a dedicated partner gene. Away from the enzymes, several measurements medicine leans on were audited today, from the guarantee behind every q-value to the lung-function endpoint that decided two trials in one afternoon.Sources: https://lucafusarbassini.org/d/2026-10-13

Today's items line up along one chain. A phone-mounted fundus camera with offline AI screened more than a thousand people in Liberia, and a label-free whole-blood imager was tried on sepsis in an intensive care unit. The UK accepted all 44 recommendations of its AI commission, including monitoring devices "throughout their working life", and Zambia showed a regulator can approve a drug in 12 working days by relying on reviews already done elsewhere. Against that, Gilbert Welch argues Grail's multicancer blood test found more cancers without reducing late-stage disease, and Helen Pearson shows science often already holds the answer and fails to add it up. The measurement is getting cheap. What decides whether it helps is calibration, synthesis, lifecycle approval and the choice of endpoint.Sources: https://lucafusarbassini.org/d/2026-10-12

How about play in animals?
 
Today I have the pleasure to discuss outstanding research in ethology with Elisabetta Palagi from the University of Pisa, who has been a leader in Primatology for over 30 years, and, among several successes, was recently awarded the Animal Behavior Society Fellowship Award for her outstanding research.
 
In this episode, we explore animal play behavior, focusing on social play. We examine its definition and functions across different animal groups, gaining insights into its diverse manifestations. We delve into the methodologies used by ethologists to study play and its decline as animals mature. We discuss the paradoxical nature of play, its role in social competence development, and its significance among infant chimpanzees. Communication and rough-and-tumble play are explored, along with self-handicapping and the enduring importance of play in adulthood. We compare playfulness in bonobos and chimpanzees and investigate facial expressions and mimicry in play and sexual behavior. This journey unravels the evolutionary significance of play, communication dynamics, and its impact on social bonds in animal societies.
 
If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM or email me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini. Elisabetta Palagi’s picture is by Luca Ragaini.
RESOURCES
[ACADEMIC] Rough-and-tumble play as a window on animal communication: https://onlinelibrary.wiley.com/doi/abs/10.1111/brv.12172#:~:text=ABSTRACT,of%20escalation%20to%20serious%20fighting.
[ACADEMIC] Not just for fun! Social play as a springboard for adult social competence in human and non-human primates: https://link.springer.com/article/10.1007/s00265-018-2506-6
[ACADEMIC] Mirror replication of sexual facial expressions increases the success of sexual contacts in bonobos: https://www.nature.com/articles/s41598-020-75790-3#:~:text=In%20bonobos%2C%20during%20sex%20RFM,%2D%20and%20hetero%2Dsexual%20interactions

What if we had a ChatGPT for transcriptomics, what if we could predict how the gene network is changed in diseases for which we have scarce molecular data?
Today I have the immense pleasure to discuss transformers in single-cell transcriptomics to make huge predictions about gene modulation with Christina Theodoris, who today first-authored a paper in Nature entitled “Transfer learning enables predictions in network biology”. Christina has recently started her own lab at Gladstone Institutes to study gene networks with a focus on the heart and cardiovascular disease, after working at Harvard, the Broad, and Children’s.
Christina and I discuss in an entertaining and technical conversation her impressive model, GENEFORMER.  We introduce foundational concepts in machine learning that enabled her work: pre-training on large scale datasets and transfer learning followed by task-specific fine tuning, to democratize fundamental knowledge; rank value encodings; self-attention; masked learning objectives and self-supervision; embeddings. Christina pooled the huge amount of RNA-seq transcriptomic data generated worldwide at the single-cell level in recent years so to make a model that knows the gene-gene expression correlations, for all the cell types in the human body, and understands their gene networks so well that it can predict how they rewire and genes change expression when you perturb single genes or combinations of them. We discuss current applications, such as in silico reprogramming and differentiation, in silico deletion of genes or modeling of dosage reduction or increase for the study of haploinsufficiencies. Christina beautifully explains how such a fine-grained network view of single-cell biology can help us identify key genes to normalize by medical intervention to restore health in disease settings. Her model is powerful to understand the genome-wide, all-tissues expressive consequences of diseases for which only a limited amount of data is available, thanks to transfer learning, it can model the effect of treatments that modulate the expression of specific genes, and it is so promising for understanding in depth rare diseases and more, including cardiovascular diseases as shown in the first report. We end by speculating on the broad applicability of her model, and the possibilities of growth, for instance by integrating several omics data, towards the dream of generating entire virtual patients starting simply from their DNA sequence. I honestly can’t make predictions about what Christina and her colleagues will do in the next few years, as their GENEFORMER is completely out of what I thought was already coming!
If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.
[ACADEMIC] “Attention is all you need”: https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf
Christina’s lab: https://gladstone.org/people/christina-theodoris
[ACADEMIC] Transfer learning enables predictions in network biology: https://www.nature.com/articles/s41586-023-06139-9
 

What if told you that your lifespan is probably predictable from a biopsy?
Today I have the pleasure to discuss state-of-the-art epigenetic clocks for biological age and lifespan estimation to develop interventions that slow down aging with my former mentor Professor Alessandro Cellerino. Prof Cellerino is a world leader in aging and longevity research. He is an Associate Professor and Research group leader at the Scuola Normale Superiore in Pisa and the Leibniz Institute on Aging.
Prof Cellerino and I discuss how he and his collaborators established quickly and with great success Nothobranchius furzeri, Killifish for friends, as a model organism for aging research, so to test pharmacological and non-pharmacological interventions with the hope to slow down or reverse the aging process. But this needs to measure aging and how fast it proceeds for different individuals, leading us to discuss epigenetic clocks, which might effectively predict your biological age from a simple biopsy from your skin! So if you happen to have a biological age which is more than your chronological age, take action, it means you are aging faster than your same-year old high-school peers! We discuss how striking the RNA-seq revolution has been also for the aging field, how conditions that result in faster or slower aging are probably often set early, much before the aging process begins. We analyze some of the common machine learning techniques employed by epigenetic clocks, and the difficulties to infer causality and identify crucial genes, as several different combinations of relatively few genes can all equally well predict biological age. Finally, we reason on the importance of multi-species clocks for translational research: clocks that work both in model organisms and in humans, such as the transcriptiomic clock just published by Ferrari et al. in the Cellerino Lab, which employs an innovative architecture to control for the effect of confounders such as sex on the age prediction. Looking forward to seeing what Prof Cellerino and the Cellerino lab achieve in the next few years!
If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM or email me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.
RESOURCES
[ACADEMIC – a great paper illustrating the role of the Nothobranchius furzeri “Killifish” in aging research] Longitudinal RNA-Seq Analysis of Vertebrate Aging Identifies Mitochondrial Complex I as a Small-Molecule-Sensitive Modifier of Lifespan: https://www.cell.com/fulltext/S2405-4712(16)30030-8
[ACADEMIC] A deep neural network provides an ultraprecise multi-tissue transcriptomic clock for the short-lived fish Nothobranchius furzeri and identifies predicitive genes translatable to human aging: https://www.biorxiv.org/content/10.1101/2022.11.26.517610v1
[ACADEMIC, foundational review on epigenetic clocks] DNA methylation-based biomarkers and the epigenetic clock theory of ageing: https://www.nature.com/articles/s41576-018-0004-3
The Cellerino Lab: https://www.leibniz-fli.de/research/associated-research-groups/cellerino/current-projects-and-team
 

What if gene editing went on a date with nanomedicine?
Today I am lucky to spend some time talking to my former mentor Vittoria Raffa about all the fundamental molecular biology of gene editing, and the open challenges to translate CRISPR-based technologies to the clinic. Will nanomedicine and synthetic biology be the right partners for gene editing to make it? Vittoria is an Associate Professor of Nanomedicine and Molecular Biology at the University of Pisa, and she’s been a leader in nanomedicine since a very young age.
Vittoria and I start from her experience as the coordinator of the European project I-GENE, which provides a great example to today’s episode, as it combines gene editing, nanomedicine, and synthetic biology concepts. The I-GENE Project is building, specifically, a light-switchable nanoformulation for gene editing, to be first used for melanoma. Vittoria and I discuss the main CRISPR-based technologies, including “traditional” editing with CRISPR/Cas9 and its natural and evolved or engineered variants, base editors, prime editors, PASTE editors, CRISPRa/i. We consider the main open challenges to broadly translate gene editing to the clinic: delivery, off-target toxicity, immunogenicity, cost, and more. Vittoria beautifully explains why the current number of 26 clinical trials, even if huge for how long ago this technology was invented, is less than what can be done: CRISPR-based gene editors are mostly delivered by viral vectors, which cost a lot to make. She suggests that the widespread deployment of nanomedical devices could greatly reduce the cost of therapies, hence accelerating the development of CRISPR medicines for more and more diseases, and at an affordable cost. She then guides us through recent concepts in synthetic biology, especially to build nanomedical tools that recognize multiple cellular inputs and release the drug, such as the gene editor, only when a number of logic gates turn true. I’ll stop here, there’s so much more to discover in our conversation! Looking forward to seeing what Vittoria and the Raffa lab achieve in the next few years!
If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.
[ACADEMIC, outstanding review on most of the state of the gene editing field with a focus on medical applications] Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors: https://www.nature.com/articles/s41587-020-0561-9
[ACADEMIC REVIEW] CRISPR/Cas9 in the era of nanomedicine and synthetic biology: https://www.sciencedirect.com/science/article/pii/S1359644622003683
The I-GENE Project that Vittoria coordinates: https://i-geneproject.eu/
[OUTREACH] CRISPR clinical trials, 2022 Update by the Innovative Genomics Institute: https://innovativegenomics.org/news/crispr-clinical-trials-2022/
 

What’s the revolution of synthetic biology and metabolic engineering in Industrial Biotech?
Welcome to the latest episode of The Biotech Futurist, where we drive around the fascinating field of industrial biotechnology. Today, I have the pleasure of interviewing Stefano Bertacchi, a passionate researcher and EU bioeconomy ambassador. Stefano shares with us his journey, from his interest in microorganisms and yeasts to his current research in industrial biotechnology.
Stefano introduces us to the main themes, goals, and research directions in the field of industrial biotechnology. We explore the biotech story behind everyday products that we tend to forget about and the contribution of biorefineries to sustainable and circular economies. We delve into lignocellulosic biomasses, which are interesting in a bioeconomy setting as a preferred feedstock for biorefineries. Stefano explains the concepts of separate hydrolysis and fermentation and simultaneous saccharification and fermentation, their timing, and the useful products that can be obtained.
We learn about bioreactors, their workings, and examples of Stefano's favorite microorganisms deployed by biorefineries. Stefano shares how they are discovered, optimized, engineered, and evolved, and the difference between adaptive laboratory evolution (ALE) and directed evolution. We discuss the microbial synthesis of organic acids as a key example of industrial biotech processes, evaluating different substrates, and building a new industrial biotechnology, taking into account the value chain, downstream purification, and testing small batches in academia.
Stefano also shares his views on the emerging and revolutionary role of synthetic biology and metabolic engineering. We explore Stefano's everyday life as a researcher in industrial biotech and his role as an EU bioeconomy ambassador and public figure in science outreach in Italy. Stefano finally shows us the power of memes for science communication.
If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM or email me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.
 

I am delighted to host Jenna Pucel for a short bonus episode on ableism, a urgent topic in bioethics, strongly connected with this week's theme, genetic counseling. Excited to keep having conversations with Jenna and people like her!