For years, clinicians have taken a trial-and-error approach to many medical treatments for mental illness. If a patient doesn't respond to a particular drug, providers will often move onto another, sometimes not driven by insight into an individual's needs or specific symptoms.

"I've always been perplexed at how we are supposed to treat all these manifestations with the same treatment," Dr. Hans Eriksson, chief clinical development officer at HMNC Brain Health, said in an interview with Healthcare IT News. "It has very much been a one-size-fits-all [approach] in the pharma industry."

Eriksson, a psychiatrist by training, has been working in the pharmaceutical industry for more than 20 years. Initially, he worked on what he calls more traditional compounds aimed at treating mental illness: those that would become Lexapro, Seroquel and Rexulti.

Later, he was chief medical officer at the London-based Compass Pathways, where he contributed to the therapeutic development of psilocybin, the active compound in so-called magic mushrooms.

Now, at Munich-headquartered HMNC, he and his team are trying to leverage precision psychiatry to target the use of medication and, ultimately, improve patient outcomes. Their ABCB1 test, which seeks to predict the clinical response of patients to commonly prescribed medications, is currently on the market in Germany, Switzerland and France.

"What lies at the core of what we are doing is essentially the insight that many psychiatric conditions, as we diagnose them, are very heterogeneous," he said. "We make a diagnosis of schizophrenia or bipolar disorder or major depressive disorder, without recognizing that there is a vast variability in the clinical manifestations."

A patient can be classified as having major depressive disorder, he explained, if they wake up early, have difficulty sleeping, eat little, lose weight and feel very sad. But another person can sleep a lot, wake up late in the morning, eat more than usual, gain weight and feel sad – and still be diagnosed with the same illness.

"Our thinking is that many of these psychiatric disorders have subsets of individuals that would respond particularly well to certain interventions," he said. "The trick is just to find the intervention and to find the individuals."

"Which is a bit tricky," he added. "But we believe that it can be done in many cases."

At this point, Eriksson explained, the company is aiming to pair tests with medications, with the help of machine learning.

"Right now, we're talking about genetic tests because we have two products that have companion diagnostic tests in our company, but we are also clear on the fact that you could use any type of information that comes from an individual," he explained.

Eventually, he said, "You can use proteomics data, looking at the proteins in the blood; you could look at transcriptomics to see what genes are transcribed; you could look at cognition, psychological variables, and feed this information into an algorithm to find the patients that are more likely to respond to certain intervention.

"This process could be driven by an insight into the [treatment] mechanisms, but it could also be completely agnostic," he said. "You could actually just tell a machine learning system to find the individuals that have a common characteristic that matches the ability to respond to certain interventions."

"That's the way we want to progress right now," he said.

Eriksson drew attention to one of HMNC's programs, Nelivabon, which includes a compound, nelivaptan, that has the ability to calm a hyperactive stress system – a characteristic for many depressed patients. Working with the Max Planck Institute in Munich, HMNC found a common genetic signature in individuals with this characteristic.

"So, now, we not only have the medication, we also have the tool to find the individuals, and now is the point in time where we can start playing precision psychiatry," said Eriksson.

The project is entering a Phase II proof of concept study in the first quarter of 2022.

"So, this is the thinking: To find subsets of individuals using biological tools or psychological tools, and hopefully, in the future, to identify this subset, and then offer them a treatment that is specifically tailored to that biological finding," Eriksson said.

Eriksson also noted the potential advantages of more seemingly unconventional medications, such as LSD and MDMA (commonly called Ecstasy or Molly), to treat depression.

"I think we are in a very exciting period – I would call it the second golden age – of psychopharmacology," he said. "And it's quite interesting that much of the new medications that are tested today actually come from areas outside of ordinary medicine.

"Many of these compounds that are in development now have been used in underground communities – some have even been abused previously," he said. "But all of these are compounds with profound psychotropic effects. I think if we harness these effects in a responsible way, and make sure that they can get to patients who really need them, we can really make a difference."

He said HMNC is interested in developing a genetic test to find patients who would have particularly good reactions to these kinds of treatments and would be less likely to experience negative side effects.

"In an ideal world, we would like to be able to say, 'Yes, you will probably respond to ketamine. And you're not likely to get any side effects.' 'You're an obvious candidate, you might respond, but you're also at high risk of having the side effects, maybe you should have something else.'"

"And I think it's all about the provider of the medication – whether that's the physician or the pharmaceutical company – not to push the medication on every patient because, in the long run, that is not what is beneficial," he said. "What makes good medical sales, and probably also in the long run makes good business, is to give the right medication to the right patient."

Overall, he said, a variety of factors are driving a potentially innovative approach to treating depression and other mental health disorders.

"I think there is a clear reduction of stigma. I think people are talking much more freely about mental disorders, recognizing that they are extremely common," he said.

"Part of the excitement is that we are not so limited today by preconceived notions" around treatments such as psilocybin, LSD and MDMA, he added.

"Today, it's comparatively cheap to do genetic analysis; the costs have gone down dramatically. We see a situation where these analyses may be moved closer to the physician's offices," he continued. "We are getting more sophisticated AI approaches."

In the future, he said, "I hope we can integrate more sources of data," going beyond genetic analysis to include more proteomics.

"If we could get to the right medication earlier, it would be very helpful to individuals because depression is a really painful state," he said.

Kat Jercich is senior editor of Healthcare IT News.
Twitter: @kjercich
Email: kjercich@himss.org
Healthcare IT News is a HIMSS Media publication.