Monthly report – January 2025

Welcome to the first issue of Project BioLogical! Every issue, we open with a monthly report that sums up three major developments in medicine and the life sciences from the past month, in this case from the end of 2024 to the beginning of 2025. These updates usually carry some great deal of societal significance, or otherwise serve to address often-overlooked ideas and misconceptions we may encounter in our day-to-day lives.

In this issue, our monthly report focuses on the instruments we use to process information – our brains and our computers. This is quite the timely topic, seeing how the latest Nobel prize was won with a breakthrough in bioinformatics. AI, too, is a rising force that has dominated headlines – and medical journals – for more than a year now.

In this report, we’re going to talk about fresh ways to view psychedelic treatments, in light of the FDA’s rejection of the use of MDMA to treat PTSD. We also look at the dangers of AI in medicine, as well as key lessons we can learn about medical statistics as a whole. Finally, we’ll gain a little insight into how our brains process information and output it, dispelling a common myth along the way.

Psychedelics and autism

In September last year, the FDA sent a Complete Response Letter for the use of psychedelics such as MDMA in treating Post-Traumatic Stress Disorder, or PTSD. In other words, the treatment was rejected for being insufficiently trialled. New frontiers in science are exciting, and efforts to further research in these branches generally do not go unrewarded. But outside of the FDA, psychedelic medicine is preceded by a reputation of terror. A long history dating back to shamanic rituals 10,000 years ago unveil a rooted and terrifying patchwork of induced hallucinations, drug addiction, otherworldly experiences – the list goes on. And yet, even amid the throes of naysayers, drug treatment is slowly gaining a foothold in the world of modern medicine.

The truth is not nearly as dramatic as it seems. Many researchers have taken the initiative to clear up doubts and stigma surrounding psychoactive drugs. Aaron Paul Orsini explains that many adverse effects with psychedelics come with negative and uncontrolled contexts – taking drugs illegally, for instance. Under safe conditions, the psychedelic treatment is administered with close medical supervision to ensure the patient doesn’t get hooked, as well as professional efforts to minimise the impact of a “bad trip”.

However, this taboo treatment has recently found promise amongst a widely forgotten demographic: Autistic people. These neurodivergent individuals are prone to ostracism and high stress from having to handle functioning in a society that is built for neurotypicals, resulting in much higher rates of anxiety and depression.

Recent small trials have shown unique insights, however. 82% of autistic people in one test had less psychological distress and 78% experienced less anxiety when dealing with people after psychedelic treatments; another showed rapid and long-lasting alleviation of social anxiety after six months of psychedelic treatment.

Of course, not everything is so simple. The truth is neurodiversity results in differing experiences for differently wired brains, and so not everyone has the same response to psychedelics. Orsini notes that neurotypicals tend to have different responses across the board from autistic people, and even individual differences amongst autistic people can result in a drug that allows one person to relieve their anxiety can create terrifying waking nightmares for another. While it is true that autism and psychedelics both ought to be destigmatised, the fact remains that the latter is not yet researched to maturity, and time must still be taken to assure its safety in terms of dosage, management of side effects and, ultimately, effectiveness.

Responsible AI doctors

With AI seemingly taking every industry by storm, it is inevitable that it is now being used in medicine for a variety of sophisticated purposes. Crunching big data, generating patient vignettes or case studies and even diagnosis are roles that have been dreamed up for this rising technology, but it is now more clear than ever that great care and responsibility has to be taken to ensure it is trained to be unbiased and fair.

The Lancet has revealed some shocking metadata: 6 out of 1518 studies on Covid-19 in one national database recorded ethnicity data, while in another less than a quarter of 192 studies collected demographic information on sex, gender, ethnicity or race.

It is known that different demographic groups are more prone to certain diseases and conditions due to subtle genetic differences, and they often tend to present these illnesses differently as well. With AI being trained on databases with incomplete or nonexistent demographic information, there is an undeniable risk that the diagnoses, recommendations or vignettes it generates will be biased to only represent the majority group that dominate the databases around the world, without being able to analyse any trends in population subgroups and minorities. These observations bring tidings of a sober prospect for many AI scientists: that this technology cannot work for every individual.

Denniston et al argue that the biggest issue with applying AI is generalisability – how can one model from the same manufacturer address the problems faced by a hospital in Edinburgh, Scotland just as well as one in Bamako, Mali? While current regulations place responsibility on the manufacturer to make use of their existing databases to assure fairness, the fact is that these databases are lacking. The truth is that healthcare institutions have to make use of their own data, too, to help make up for the shortage of resources and help personalise AI to their own localities. Otherwise, too many will fall through the gaps.

The brain is slow!

You might feel as though your mind is filled with what seems to be infinitely colourful and rich experiences. What you would be wrong to think, however, is that the human brain is some superfast computer that outpaces our greatest technological achievements (as a certain Elon Musk thought). In fact, while we receive information in the ballpark of several hundred million to billions of bits per second, our brains only think proper (i.e. process and output information) at about ten bits per second.

Elon Musk described his experience with a “bandwidth problem”, wherein he believed his brain was producing information at a rate far greater than he could ever express. This sentiment, if only at an intuitive level, is actually a well-received notion to explain some of our more speedy and complex thought processes. After all, our dear readers have probably experienced an overwhelming volume of thought before in the form of a gushing rant, idea or even during critical decision-making.

To hit pause on that train of thought, neuroscientists have proven that the brain has a way of tricking you into thinking it works more than it really does (kind of like some students and their parents). As counter-intuitive as it sounds, Meister and Zheng report that the outer brain is responsible for processing huge amounts of sensory data from the world around us, but siphons this load down to one thing to focus on in the inner brain, that measly 10 bits per second processing you actually get to perceive. What’s the reason? No conclusive explanation exists yet. It is equally confusing to note that there is barely an evolutionary advantage of being able to process just one tiny thing at a time. The neuroscience community, however, is clearly on the verge of a thought-defining insight.

That’s a wrap for Project Biological’s January report, and we’ll see you again in the rest of our articles as well as in our future issues!

References:

1. Nuwer, R. (2024, December 17). Could psychedelic drugs improve the mental health of ... https://www.science.org/content/article/could-psychedelic-drugs-improve-mental-health-autistic-people

2. The Lancet Digital Health. (2025, January). The Lancet | The best science for better lives. A long STANDING commitment to improving health care. https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00272-3/fulltext

3. Denniston et al. (2024, May), Responsible and evidence-based AI: 5 years on, The Lancet Digital Health, Volume 6, Issue 5, e305 - e307, https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00071-2/fulltext

4. Nuwer, R. (2024, December 17). The human brain operates at a stunningly slow pace. Scientific American. https://www.scientificamerican.com/article/the-human-brain-operates-at-a-stunningly-slow-pace/