NHS England has asked the Trust implement these features on behalf of 11 other trusts also using the SystmOne electronic patient record
Royal Surrey NHS Foundation Trust deploys ophthalmology EPR
Royal Surrey NHS Foundation Trust has gone live with an ophthalmology electronic patient record (EPR) system from Medisoft.
The Effectiveness and Acceptability of Formal Versus Informal Mindful Self-Compassion for Adolescents
Conditions: Coping
Interventions: Behavioral: Formal Mindful Self-Compassion (MSC-F); Behavioral: Informal Mindful Self-Compassion (MSC-I)
Sponsors: Cambridge Health Alliance
Not yet recruiting
Interventions: Behavioral: Formal Mindful Self-Compassion (MSC-F); Behavioral: Informal Mindful Self-Compassion (MSC-I)
Sponsors: Cambridge Health Alliance
Not yet recruiting
Top 5 Firms Engineering Healthcare in the CNS Space
Central nervous system (CNS) treatments are having a major comeback. These five precision medicine players plan to ride the resurgence.
After a decade of stagnation, the CNS space is seeing a revival in sales and R&D spending as the market was last year projected to surpass $80 billion for the first time since 2013 and hit around $127 billion.
Recent landmark approvals have brought attention back to the CNS, including the U.S. Food and Drug Administration (FDA)’s greenlight of Eisai/Biogen’s lecanemab (Leqembi) for the treatment of Alzheimer’s disease in 2023, and the FDA approval of Bristol-Myers Squibb’s schizophrenia treatment xanomeline/trospium chloride (Cobenfy) in 2024.
At the same time, Johnson & Johnson’s depression treatment, esketamine (Spravato), is on its way to blockbuster status, showcasing the growth potential of the CNS market.
These successes accompany an emerging shift in psychiatry clinical trials from subjective rating scales to more objective endpoints, including digital and physiological measures, with the potential to better tailor treatments to a patient’s biological makeup.
Startups and scaleups are attracting increasing investor attention for their potential to change the way we treat CNS conditions. Check out our list of the most exciting companies that have netted the biggest investor dollars.
1. Aerska
Founded: 2025 | Headquarters: Dublin, Ireland
Aerska’s name is derived from an Irish proverb stating that people survive in each other’s shelter, emphasising the strength of its team.
This team includes co-founder Jack O’Meara, previously co-founder of the liver-focused RNA interference (RNAi) biotech Ochre Bio, who is driven by the experience of loved ones suffering from Alzheimer’s disease.
Aerska is developing RNAi therapies for neurodegenerative conditions, including Parkinson’s and Alzheimer’s disease.
While there are already FDA-approved RNAi therapies on the market, such as Alnylam’s patisiran (Onpattro), these are typically focused on liver and cardiometabolic conditions rather than the CNS.
Aerska’s technology consists of antibody “brain shuttles” that bind to proteins on the blood-brain barrier (BBB). They then carry a payload RNA into the brain.
The payload, which is designed based on data-driven patient stratification and disease biomarkers, then silences specific genes driving the disease.
Aerska has already raised $60 million since its launch, including a $21 million seed round in October 2025 and a $39 million Series A round in February 2026, co-led by EQT Life Sciences and age1.
The company, which has research operations in the U.K., is using the latest funding to drive its pipeline programs toward clinical testing.
2. Beacon Biosignals
Founded: 2019 | Headquarters: Boston, Massachusetts, U.S.
Beacon Biosignals was co-founded by a team including its CEO—MIT neuroscientist Jacob Donoghue, MD, PhD—and its CTO, the machine learning researcher Jarrett Revels.
Boasting more than 100 employees, the company’s goal is to provide objective biomarkers in drug development that neurology and psychiatry have traditionally lacked compared with other areas of precision medicine.
Its FDA-cleared Waveband device measures the brain’s activity, known as electroencephalography (EEG), while patients sleep at home. The EEG data is then stored, quality-controlled, and fed into AI models that can guide the design of clinical trials.
For example, Beacon’s EEG data can identify patients with Alzheimer’s disease who have worse outcomes and might need a more targeted treatment or a different clinical trial than other patients.
Beacon raised $27 million in a Series A round in 2021 and an oversubscribed Series B round worth $86 million in November 2025.
The B round, which included investors such as Innoviva, Google Ventures, and Nexus NeuroTech, will help the startup to accelerate the discovery of neurobiomarkers and broaden clinical adoption of the technology.
Beacon acquired the French sleep monitoring company Dreem in 2023 to access its monitoring data and headband technology. Beacon then acquired the Ohio-based CleveMed in April 2025 to harness technology measuring breathing, oxygen, and other signals.
3. Brainomix
Founded: 2010 | Headquarters: Oxford, U.K.
Brainomix was founded by a team including CEO Michalis Papadakis, PhD, who was scientific director of the preclinical stroke lab at the University of Oxford.
Brainomix is dedicated to speeding up patient care in cases of stroke, where speedy treatment is key.
Brainomix’s flagship product, Brainomix 360 Stroke, is designed to harness AI to interpret brain scans and detect blood clots in patients with stroke, speeding up clinical decision-making.
The product involves a group of tools that automatically analyze images, including results from computed tomography (CT), CT angiography, magnetic resonance imaging (MRI), and CT perfusion.
Brainomix’s technology doubled the rate of thrombectomy treatment in patients with stroke and reduced hospital triage and transfer delays, according to a 2025 study.
The University of Oxford spinout is at a commercial stage, with operations in more than 20 countries, and is expanding into the U.S.
Brainomix raised a $21.2 million Series B round in 2021 and extended its Series C round from $6.5 million in March 2025 to $25.4 million in February 2026, with leading investors including Parkwalk Advisors and Hostplus. The proceeds will fuel the company’s expansion into the U.S. market.
Brainomix has also partnered with heavyweights, including Nvidia, Boehringer Ingelheim, Medtronic, and GE Healthcare.
Brainomix also has a product dedicated to disease monitoring in pulmonary fibrosis.
4. Circular Genomics
Founded: 2021 | Headquarters: San Diego, California, U.S.
Circular Genomics was spun out of the University of New Mexico, with its founders including CSO Nikolaos Mellios, PhD, and Alexander Hafez, PhD.
The company later moved its headquarters from Albuquerque to San Diego in March 2025 to access scientific and operational know-how from Eli Lilly at Lilly Gateway Labs.
Circular Genomics aims to equip medical professionals with a blood test to detect CNS conditions early, in addition to stratifying and guiding the treatment of patients.
Its technology involves using a polymerase chain reaction (PCR) test of a patient’s blood sample to screen for specific circular RNA molecules produced in the brain that can cross into the blood and be measured as a biomarker of disease in the CNS.
Commercially launched in 2024, Circular Genomics’ MindLight SSRI Antidepressant Response Test predicts whether a patient will benefit from common antidepressants called SSRIs with around 77% accuracy. This is designed to predict a patient’s most suitable antidepressants without needing months of trial-and-error approaches.
The company is applying its technology in Alzheimer’s disease, where the approvals of disease-modifying therapies such as Leqembi have led to demand for tests that can detect the disease at earlier stages than traditional tests.
Circular Genomics raised $15 million in a Mountain Group Partners-led Series A round in December 2025 to finance the development of its technology and expansion of its technology in Alzheimer’s disease.
The company also has its sights on other CNS conditions, including multiple sclerosis and Parkinson’s disease.
5. Omniscient Neurotechnology
Founded: 2019 | Headquarters: Sydney, Australia
Omniscient (o8t)’s founders include CMO Michael Sughrue, MD, a neurosurgeon aiming to improve anatomy maps for other surgeons, and machine learning expert Stephane Doyen, PhD.
o8t’s FDA-approved product Quicktome involves using a patient’s MRI brain scans and AI models to map out a patient’s brain circuitry. These maps, accessible from an electronic tablet, can guide surgery to minimize the risk of brain damage compared to using a generalized anatomical diagram.
Quicktome is already in use at major hospitals around the world, including major centers in the U.S. Its partners include U.S. surgical support firm META Dynamic and the U.S. medical device innovation center, The Jacobs Institute.
o8t has raised more than $60 million, and bagged $14 million (AUD 20 million) in January 2026 as part of a Series D round targeted to reach $25 million (AUD 36 million). The round was led by Australia’s National Reconstruction Fund (NRFC) and OIF Ventures, with the aim of keeping the company based in Australia.
The funding is earmarked to fuel the development and commercialization of Quicktome, and grow o8t’s Australian workforce by more than 40. The company also has operations in Atlanta, Georgia, U.S.
o8t also plans to expand the technology into high-growth markets, including brain computer interface targeting, stroke and traumatic brain injury.
Jonathan Smith, PhD, is a freelance science journalist based in the U.K. and Spain. He previously worked in Berlin as a reporter and news editor at Labiotech, a website covering the biotech industry. Prior to this, he completed a PhD in behavioral neurobiology at the University of Leicester and freelanced for the U.K. organizations Research Media and Society of Experimental Biology. He has also written for medwireNews, Biopharma Reporter, and Outsourcing Pharma.
The post Top 5 Firms Engineering Healthcare in the CNS Space appeared first on Inside Precision Medicine.
STAT+: Pharmalittle: We’re reading about Trump’s drug tariffs, a U.S.-U.K. pharma trade deal, and more
And so, another working week will soon draw to a close. Not a moment too soon, yes? This is, you may recall, our treasured signal to daydream about weekend plans. Our agenda is rather modest so far. We plan to tidy up around the castle, promenade with the official mascots, and catch up on our reading. We also plan another listening party, where the rotation will likely include this, this, this, this and this. And what about you? The change of seasons opens up all sorts of possibilities, from long walks through woods to strolling along city streets to drives through the countryside. Of course, if the weather fails to cooperate, you could open a book, watch the telly, or spin a platter and dance about. Or maybe it is an opportunity to connect with someone special. Well, whatever you do, have a grand time. But be safe. Enjoy, and see you soon. …
The Trump administration announced 100% tariffs on imported brand-name drugs — but with significant caveats, STAT explains. Many large drugmakers will not have to pay the tax because they struck deals with the U.S. to build manufacturing facilities here and lower the prices of their medications. Drugmakers that have not struck such deals but pledge to bring production to the U.S. can have tariffs reduced to 20% for the remainder of Trump’s term. The tariffs open a new front in the Trump administration’s efforts to rein in the pharmaceutical industry and in its push to bring manufacturing back to the U.S. The announcement comes as Trump has looked to emphasize his administration’s work to make prices — especially for medicines — more affordable ahead of the midterm elections.
Meanwhile, the Trump administration is negotiating more drug-pricing deals, now with smaller companies, according to STAT. The new talks offer a pathway for smaller pharmaceutical companies — those not included in the first round of deals — to pledge lower prices and potentially avoid tariffs or new pricing policies through Medicare. The negotiations suggest the administration is looking to replicate the strategy it used with larger drugmakers: extract voluntary, confidential agreements in pursuit of lower prices and more domestic manufacturing. They also offer smaller players in the sector the chance to cut a deal and gain more certainty about how they might be affected by federal policies. But the number of companies in talks with the administration remains unclear, as does whether or when the sides will reach agreement.
Hydrogel-Based Axon Model Improves Early Testing for MS Remyelination Therapies
Axons—the long, cable‑like projections that relay electrical signals across the nervous system—depend on tightly wrapped layers of myelin to keep those messages fast and reliable. When this insulation is damaged, as in multiple sclerosis (MS) and other neurodegenerative diseases, signal transmission slows and neurons eventually degenerate. Although oligodendrocytes can repair myelin early on in the process, this capacity declines with age and repeated inflammatory attacks, leaving researchers searching for therapies that can restore myelin more effectively.
A team at University College London (UCL) has now developed a more physiologically realistic way to study how myelin forms—and how potential drugs might influence that process. Their new hydrogel‑based axon model, described in Nature Methods in a paper titled “Tunable hydrogel‑based micropillar arrays for myelination studies,” recreates both the geometry and softness of real axons. The platform is designed to address a longstanding problem in the field: many drug candidates that appear promising in rigid, plastic‑based lab models ultimately fail in human trials.
“To stop MS, we need therapies that repair myelin,” said senior author Emad Moeendarbary, PhD, professor of cell mechanics and mechanobiology at UCL and CEO of BioRecode. “Promising drug candidates in the past have failed when tested in human patients. One factor might be that laboratory models do not replicate the basic physical properties of the human brain.”
The UCL team engineered vertical micropillars—each tens of times thinner than a human hair—using a microfabrication process called photolithography that allowed them to precisely tune diameter, spacing, and stiffness. Unlike earlier artificial axons made from hard polymers, these pillars are composed of polyacrylamide hydrogel, a material whose elasticity can be adjusted to match the ~5 kPa softness of native axons. As the authors noted in the paper, the system “mimics the three‑dimensional architecture and softness of axons,” enabling oligodendrocytes to form “multilayered compact myelin” around the pillars.
The researchers seeded the hydrogel pillars with human and rodent oligodendrocytes and tested several candidate remyelination drugs. When the pillars were tuned to realistic softness, drug performance dropped—suggesting that overly rigid models may have produced misleading hits in the past. “Our work suggests that commonly used rigid models, hundreds of times stiffer than real axons, can generate misleading drug hits,” Moeendarbary said. “We believe that our more life-like model can be used as a more robust early test of drug candidates and as a platform to discover new drugs.”
The study also marks the first demonstration of compact, multilayered myelin grown from human oligodendrocytes in a fully hydrogel‑based system. The platform’s design allows high‑content imaging, transcriptomic profiling, and systematic variation of mechanical cues—capabilities that could help researchers dissect how myelin forms and why it fails in disease.
Building such a soft, microscale structure was not trivial. “Hydrogel is a close mimic of living cells… but to fabricate a soft hydrogel at such a small scale is not an easy task,” Moeendarbary noted, crediting the five years of work led by PhD student Soufian Lasli and Claire Vinel, PhD.
By more faithfully recreating the physical environment of the brain, the UCL team hopes their model will provide a more reliable proving ground for remyelination therapies before they reach clinical trials.
The post Hydrogel-Based Axon Model Improves Early Testing for MS Remyelination Therapies appeared first on GEN – Genetic Engineering and Biotechnology News.
AI In Silico Multi-Omics Technique Cuts Therapeutic Development Costs
Bringing a drug from discovery through clinical trials takes too long and is too expensive, with preclinical costs alone estimated at $15 to $100 million. Employing artificial intelligence (AI) early in the process can lower those costs dramatically.
AI itself isn’t a panacea, though, Jayson Uffens, CTO and chairman of GATC Health, tells GEN. Instead, “Smart computing makes smart people smarter. There’s still a lot of expertise from people on the ground who bring a lot of value—maybe the ultimate value—to the mix.”
GATC Health, an AI-driven therapeutic discovery company, uses AI to raise the floor on opportunities to get high-potential compounds into human studies faster and thereby drive success.
Its proprietary approach to hit and lead identification and program derisking can cut preclinical development costs, according to Uffens, who maintains that the earlier AI is used in a program, the more dramatic the results.
The success GATC Health touts is based on deploying Operon
, the company’s proprietary AI platform. Operon deploys in silico models to simulate human biology and takes a multi-omics approach to analysis. That approach has allowed GATC to deliver three to five optimized compounds within six months, claims Uffens, versus the up to 48 months associated with traditional high-throughput screening methods.
Such acceleration occurs by using advanced in silico models to circumvent the “hundreds of thousands of dollars’ worth of experiments performed to get a hit and, ultimately, a lead,” Uffens says.
Rather than relying upon one huge model, he elaborates, “We attack the problem from multiple facets, looking at individual problems with various models and different architectures…and coordinate hundreds of AI models to answer different questions. That’s the starting point. There’s a lot of value in how we curate and parameterize our data in those specific contexts.”
The company also launched the Derisq AI Report, an in-depth analysis of drug candidates that highlights safety concerns, efficacy, and non-obvious risks early, while decision-makers can still modulate those risks.
This predictive intelligence layer is, in fact, a key element of GATC’s clinical trial insurance product. Underwritten by Medical and Commercial International (MCI) under the Lloyd’s of London framework, this insurance product leverages GATC’s predictive capabilities to identify risk. It reimburses the full cost of the trial if safety or efficacy endpoints aren’t met.
Typically, MCI’s preclinical trial insurance clients would provide that company with the relevant trial information, which would be run through the Derisq tool as part of their risk analysis.
Buyers for this insurance tend to be biopharma companies that aren’t large enough to self-insure their own trials. “Capital is expensive for them,” Uffens points out. “The insurance product is there to help them lower the cost of capital and open capital doors that may not be open otherwise.”
Multiomics to Discovery
What’s different about GATC’s approach to AI, Uffens says, is that “We come in, generally, as outsiders.” The founding team includes computer scientists as well as those with strong biology and genetics backgrounds, but not necessarily industry experience.
“We built our technology originally as a genetics interpretation platform,” he recalls, “and expanded it to find additional value.” The company was formed officially in 2020.
The turning point came when GATC became involved in a failed, big pharma program for addiction research.
“(The big pharma company) hadn’t found a solution, but had really valuable data and samples. A partner of ours was working with it to identify biomarkers and thought we could validate them. We discovered that not only could we validate the biomarkers, but we could also identify the therapeutic targets. That’s how we moved from multi-omics analysis into discovery,” Uffens recalls.
Moving forward, “We want to empower researchers,” he says. This means not only helping clients advance existing programs but also by identifying potentially more valuable targets.
Working with GATC
GATC’s key partners most likely will be biotech rather than big pharma, Uffens predicts. And, he notes, “We’re fairly agnostic to therapeutic area.”
“Most of our customers have called us because they want to realize the benefits of AI sooner rather than later,” Uffens says. “There is a lot of risk in the space. Folks who are willing to adopt AI at this stage…are looking for additional help before they risk more capital…” to solve particular challenges.
For a company to begin working with GATC, he explains, “The data we’re looking for is very similar to what they would include in an Investigational New Drug (IND) package. The earlier they are in the process, the less data they will have, but, at a minimum, we need some particulars on their therapeutic’s chemistry and the intended mechanism of action.”
Challenges
Drug development is a difficult space with plentiful challenges, he admits. Therefore, “We approach things as a tech company. We iterate through a problem and find where we can succeed or fail as quickly as we can to develop a solution. We’ve gone through multiple generations of architectures, finding ways that work best.”
The next milestone is to accumulate multiple successes with Operon and Derisq in human trials. “‘Wins in humans’ is our [next] frontier,” he says. That includes wins for its insurance underwriting partners as well as for companies working directly with GATC to advance therapeutics to human trials.
As part of that goal, GATC and BioAtla are closing a deal for a Phase III trial of ozuriftamab vedotin for oropharyngeal squamous cell carcinoma and to further develop conditionally active biologic senolytic therapies. Termed a special purpose vehicle transaction—a financial entity designed to hold specific assets that last for the life of the project—the $40 million deal formed Inversagen AI, LLC, to leverage the strengths of the founding companies.
“GATC and BioAtla are equal partners in Inversagen,” Uffens says. “GATC will own a percentage of ozuriftamab vedotin and a larger stake in future joint discoveries,” thus potentially discovering new therapeutic combinations that may be effective as conditionally active biologics.
Currently, the GATC is fine-tuning its own project prioritization. “The AI landscape is both beneficial and challenging,” Uffens acknowledges. “People have certain expectations about what AI can and should do, how it works, and how they might adopt it. Getting them to hear our unique perspective comes back to our focus on wins in humans.”
The post AI <i>In Silico</i> Multi-Omics Technique Cuts Therapeutic Development Costs appeared first on GEN – Genetic Engineering and Biotechnology News.
Digital Health Coffee Time Briefing ☕
Today’s briefing features a free digital platform built for unpaid carers in the UK and an AI-enabled platform for eating disorder services.
Commercial or industrial use of mental health data for research: primer and best-practice guidelines from the DATAMIND patient/public Lived Experience Advisory Group
BackgroundRoutinely collected health data, such as that held by United Kingdom (UK) national health services (NHS), has important research uses. However, its use requires public trust and transparency. Access by commercial/industrial organisations is especially sensitive for the public, as is mental health (MH) data. Although existing MH data science guidelines emphasise patient/public involvement (PPI), they do not cover commercial uses specifically.ObjectivesTo develop patient- and public-led guidelines for the commercial and industrial use of MH data for research. Though UK-focused, their principles may apply internationally.MethodsA PPI Lived Experience Advisory Group (LEAG) was created within DATAMIND, a UK data hub for MH informatics. Initial discussion yielded a requirement for definitions and explanations of concepts relating to MH data research, developed iteratively. Subsequently, the LEAG developed guidelines via a qualitative quasi-Delphi approach. The agreed scope excluded data provided for research with informed consent, data processing arrangements (e.g. companies hosting electronic systems on the instruction of health services), and compliance with legal minimum requirements. The scope included the use of routinely collected MH data for research by commercial/industrial organisations without explicit consent, and aspects of industry-led MH data collection conducted with consent.ResultsAlongside the primer in MH data research concepts, the LEAG provide best-practice guidelines relating to commercial/industrial research use of MH data, for organisations controlling MH data (such as NHS bodies) and for commercial applicants seeking access. Core principles include transparency, patient rights, meaningful PPI, stringent governance, and statistical disclosure control. The guidelines recommend a risk–benefit approach to assessing data access applications, within limits that include avoiding the export of unconsented patient-level data outside NHS-controlled secure data environments, and not providing commercial applicants with access to unconsented free-text MH data. Further recommendations for NHS executive and regulatory bodies relate to public choice and transparency, clarity of guidance to research-active NHS organisations, and support for de-identification.ConclusionsMH data research requires patient/public involvement and understanding. These guidelines reflect the views of people with personal or family experience of mental ill health. We hope they are useful to the MH research community and increase public transparency and trust.
Hertfordshire Community NHS Trust to roll out AI-scribing
Hertfordshire Community NHS Trust is rolling out ambient voice technology following a pilot in community and mental health services.