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Legalisation Victory Yet Persistent Access BarriersThe UK Parliament recently approved medical cannabis, heralded as a breakthrough for patients with severe conditions. However, families such as Hannah Deacon and her son Alfie illustrate that legal change has not translated into easy, affordable treatment through the NHS.From Personal Tragedy to Advocacy: Deacon’s Fight for Her SonIn summer 2012, infant Alfie suffered relentless seizures that escalated to life‑support in Stoke hospital. After exhausting conventional care, Deacon turned to online research, discovering early reports of cannabis‑based epilepsy treatments. Her relentless advocacy helped push the national conversation that eventually led to legalisation.Growth of Private Medical Cannabis Clinics in the UKSince the policy shift, the private sector has expanded rapidly:More than 30 private clinics now prescribe medical cannabis across cities such as Sunderland, Leicester and London.Commercial advertising appears on the London Underground and billboards, promoting CBD products linked to celebrities like Claudia Winkleman and Anthony Joshua.Despite the private boom, NHS prescriptions remain scarce, with most patients still reliant on out‑of‑pocket purchases.NHS Prescription Bottlenecks and Patient RealitiesThe public health system faces several hurdles:Stringent scheduling of cannabis as a Class 1 drug limits prescriber confidence.Limited specialist pathways mean many families must navigate complex referral processes.Cost barriers persist, as NHS funding for cannabis‑based medicines is minimal compared with private alternatives.What the Next Phase of UK Medical Cannabis Policy Might Look LikeLooking ahead, experts suggest three possible developments:Clearer clinical guidelines could encourage more GPs to prescribe safely.Increased funding for NHS‑approved cannabis products may reduce reliance on costly private clinics.Continued advocacy from patients and historians—recalling pioneers like William O’Shaughnessy—could shape future legislative refinements.

Researchers at Cortical Labs in Melbourne have created a 'biological computer' using living human tissue, which can play the 1993 shooter game Doom. The team used 10ml of blood from CEO Hon Weng Chong to harvest 100 white blood cells, which were then reprogrammed into induced pluripotent stem cells (iPSCs). These cells were used to create a dish of 200,000 neurons that can interface with a computer system.The brain cells were taught to play Doom by encoding game state information, passing it through a neural network, and converting it into signals the neurons can understand. The neurons then fire an output, which the system decodes and converts back into actions in the game. This process is similar to how humans operate, with information going into the retina, being converted into electrical signals, processed in the brain, and resulting in an output.While the achievement has sparked concerns about sentience and consciousness, Chong believes the brain cells are not conscious, stating, 'At first it didn’t know how to move, aim or shoot. Then it would shoot two enemies and stop. So it’s definitely learning.' The next step could be integrating this technology with Neuralink, a brain-machine interface developed by Elon Musk.The application of biological computing lies not in gaming, but in medicine, such as disease modeling for conditions like epilepsy. This technology could allow for personalized drug testing and tailored treatments. Meanwhile, Eon Systems in San Francisco has created a virtual insect brain that can behave like a real fly, challenging the assumption that intelligence must be acquired.Biological systems like these could eventually power robots, drones, and other machines that need to navigate complex environments. As Chong notes, 'Abstract reasoning, mathematics and language are relatively recent in evolutionary terms... but motor control and probabilistic decision-making are things we’ve inherited through millions of years of evolution.' While we're far from uploading human consciousness into the internet, this technology marks a significant step in the development of biological computing.