Why personalized gene editing, genetic resurrections and embryo scoring made our list. Earlier this week, published its annual list of Ten Breakthrough Technologies. As always, it features technologies that made the news last year, and which--for better or worse--stand to make waves in the coming years. They're the technologies you should really be paying attention to. This year's list includes tech that's set to transform the energy industry, artificial intelligence, space travel --and of course biotech and health. Our breakthrough biotechnologies for 2026 involve editing a baby's genes and, separately, resurrecting genes from ancient species.

Plus: This company is developing gene therapies for muscle growth, erectile dysfunction, and "radical longevity" For decades, lithium-ion batteries have powered our phones, laptops, and electric vehicles. But lithium's limited supply and volatile price have led the industry to seek more resilient alternatives. They work much like lithium-ion ones: they store and release energy by shuttling ions between two electrodes. But unlike lithium, a somewhat rare element that is currently mined in only a handful of countries, sodium is cheap and found everywhere. Read why it's poised to become more important to our energy future. Sodium-ion batteries are one of 10 Breakthrough Technologies this year.

In the past 20 years, mice with glowing cables sprouting from their heads have become a staple of neuroscience. They reflect the rise of optogenetics, in which neurons are engineered to contain light-sensitive proteins called opsins, allowing pulses of light to turn them on or off. The method has powered thousands of basic experiments into the brain circuits that drive behavior and underlie disease. As this research tool matured, hopes arose for using it as a treatment, too. Compared with the electrical or magnetic brain stimulation approaches already in use, optogenetics offers a way to more precisely target and manipulate the exact cell types underlying brain disorders.

For a moment, I fell under the spell of Bryan Johnson. Bathed in early-morning sunlight, the 46-year-old L.A.-based tech centimillionaire and longevity celebrity didn't look much younger than his age, although he claims to have the wrinkles of a 10-year-old and organs that are several years younger than his lifespan. We were standing at the Temescal Canyon trailhead in Pacific Palisades on Jan. 13, ahead of a Johnson-sponsored "Don't Die" hike, one of many organized across the world that day and the only one hosted by him. Of the 500-plus people who had RSVP'd for the L.A. event, about 200 showed up. Some had slept in their cars to make it.

Ilya Sutskever, OpenAI's cofounder and chief scientist, is no longer focusing on building the next generation of his company's flagship generative AI models. Instead his new priority is to figure out how to stop an artificial superintelligence (a hypothetical future technology he sees coming with the foresight of a true believer) from going rogue. A lot of what Sutskever says is wild. But not nearly as wild as it would have sounded just one or two years ago. He thinks ChatGPT just might be conscious (if you squint).

Identifying patients'outside the clinic' can provide significant benefits for researchers and population health managers. Better understanding of patient cohorts can shed light on patient journeys, help optimize decisions around treatment choice and timing and inform the development of new therapies and intervention programs. Even without'in-clinic' insight - the ability to directly interact with the patient, to confirm their membership in a cohort - we have plenty of population-level tools we can use to try to identify patients. Even so, patient identification in many cases can become a challenging, even impossible task. For example, we may want to find a cohort with a certain health condition: in the simplest circumstances, if the condition is well-documented in structured medical records, we can query large real-world datasets to isolate the cohort using standardized coding.

Over the past seven years, Bayer's investment arm has infused 50-plus companies with more than €1.3 billion. Leaps by Bayer is accelerating its dealmaking pace and Bayer is committing another €1.3 billion, which the multinational corporation estimates will fuel its investment vehicle for two more years. Bayer announced the capital commitment on Friday during the company's Breakthrough Innovation Forum, an event that covered the corporation's plans in healthcare and agriculture. Those two fields were the core focus areas when Bayer formed Leaps in 2015, aiming to invest in companies developing breakthrough solutions to big challenges facing humanity, challenges that the corporation termed "leaps." At the start, Bayer identified 10 leaps.

The advent of more advanced technologies in AI and more modern development in programming such as Machine Learning, Deep Learning, Reinforcement Learning can help develop age predictors which can offer tremendous possibilities in anti-aging research. The undesirable effects of aging thus are in the process of elimination and a new era is in the making where AI is set to flourish in the healthcare industry and pharmaceutical development and research practices. Human aging is a series of physiological changes taking place in the body leading to senescence, deterioration of biological functions, different organs, and also of the ability to perceive and adapt to metabolic stress. It's the degenerative gradual process through which any living organism comprised of tissues and cells, nears its end. Aging is a universally occurring common phenomenon, which brings a lot of undesirable side effects as age-related diseases along with it such as reduced energy, hearing and vision loss, loss of memory, and inefficient metabolism to name a few.

This opinion piece is inspired by the old Danish proverb: "Making predictions is hard, especially about the future" (1). As every reader knows, the momentum of artificial intelligence (AI) and the eventual implementation of deep learning models seem assured. Some pundits have gone considerably further, however, and predicted a sweeping AI takeover of radiology. Although many radiologists support AI and believe it will enable greater efficiency, a recent study of medical students found very different reactions (2). While such doomsday predictions are understandably attention-grabbing, they are highly unlikely, at least in the short term.

While social distancing has forced healthcare conferences to go virtual, it hasn't stopped startups from raising money to fund their early development efforts. Here is a list of companies that have raised money this week. A company developing machine learning algorithms in diagnostics, Dascena said Thursday that it raised $50 million in a Series B round led by Frazier Healthcare Partners, with participation from Longitude Capital, existing investor Euclidean Capital and an undisclosed investor. The company plans to use the money to advance its suite of algorithms to inform patient care strategies and improve outcomes. In addition, Dascena announced Thursday the publication of a prospective study to evaluate the effect of its machine learning algorithm in predicting severe sepsis, in the journal BMJ Health & Care Informatics.