New drug addresses long overlooked "negative" symptoms of schizophrenia
A data-driven search found a compound that shows promising results in early trials
Schizophrenia is a chronic, debilitating neuropsychiatric disorder affecting approximately 1 percent of the world’s population. This disorder is often characterized by hallucinations and delusions — for example, the portrayal of John Nash, a mathematician with schizophrenia, in the 2001 movie A Beautiful Mind is hallmarked by Nash's interactions with characters that exist only in his imagination. However, these symptoms are only one facet of the disorder.
Hallucinations and delusions are considered "positive" symptoms — those that “add” to one’s subjective experience of the world. People with schizophrenia also experience “negative” symptoms, such as losing interest and motivation in rewarding activities, withdrawing from friends and family, and the inability to concentrate or sleep. While these negative symptoms may be less evident on the outside, they can still have a debilitating effect on the person experiencing them.
The first antipsychotic drug to treat schizophrenia was synthesized in 1951, and in the 70 years since then, many others have been introduced. However, all of these drugs act through a similar pharmacological mechanism. Research has shown that, although these traditional antipsychotic medications reduce positive symptoms, they are ineffective at addressing negative symptoms. Additionally, these drugs come with a litany of worrying side effects, including cognitive impairment, motor and cardiovascular issues, and excessive weight gain. Researchers see a pressing need to improve medications to treat schizophrenia.
Now, a new drug offers the possibility of an alternative path for schizophrenia treatment development. In 2019, scientists at Sunovion Pharmaceuticals, in conjunction with Yale University, developed a new compound, SEP-363856, which acts on the brain in a completely different way from all currently-available antipsychotic medications. SEP-363856 was developed using a technique called phenotypic drug discovery, in contrast with the more standard target-based drug discovery, which is a data-driven rather than hypothesis-driven approach. This means that instead of focusing the search for a new drug compound on a specific biological target within the brain, researchers use machine learning to rapidly screen tens of thousands of possible compounds, identifying one that offers the most promise for a given task.
This kind of data-driven method is especially useful in psychiatric drug development because psychiatric disorders are often very complex and affect multiple brain circuits. In this case, an advance in machine learning techniques enabled scientists to discover a drug that branches away from traditional antipsychotics.
After extensive testing of the SEP compound in animal models, researchers recently progressed into evaluating the safety and effectiveness of this drug in humans with schizophrenia. A total of 245 people participated in this clinical trial, detailed in the New England Journal of Medicine.
Half of the participants received the SEP compound, while half received a placebo. Participants who received the new drug showed significantly greater reductions in both positive and negative schizophrenia symptoms. Additionally, the adverse side effects reported were similar between the medication and placebo groups, meaning that the drug did not cause worse side effects than patients likely would have experienced without the drug.
While these results do look extremely promising, this research is still in an early stage. In order for this medication to receive FDA approval, it will need to undergo further clinical testing. An obvious next step is to directly compare the effectiveness of the SEP compound against traditional treatments for schizophrenia rather than only against placebo. The current study is also limited by the demographics of the participants: 82 percent of the study sample was white, which is far from representative of the racial makeup of people diagnosed with schizophrenia in the general population. In fact, according to a 2014 study, "African American/Black" and "Latino American/Hispanic" individuals are diagnosed with psychotic disorders like schizophrenia at a rate approximately three times higher than their white counterparts.
The new study only involved four weeks of treatment and excluded patients who had been hospitalized more than twice for schizophrenia, meaning that the drug has not yet been tested in the most severe cases. Future clinical trials of the SEP compound must be expanded by examining the drug’s effects in a more racially diverse group, including patients with prior hospitalizations, and extending the length of the trial to look at long-term effects of the medication.
Even at an early stage, however, the development of this drug offers a new direction in the long-stagnant field of antipsychotic medications. Its effectiveness in treating negative symptoms is especially exciting, not only because these symptoms are currently under-treated, but also because they are often the first to develop: 73 percent of people with schizophrenia experience negative symptoms before the onset of positive symptoms. Therefore, having a medication that actually works to treat negative symptoms could result in earlier treatment.
Studies have shown that early treatment of schizophrenia is critically important, as early intervention can reduce the duration of untreated psychosis, while delays in treatment can increase a person's risk of brain atrophy. Additionally, the relatively minimal side effects of the SEP compound appear encouraging, as the side effects of traditional antipsychotics can be at best troubling, and at worst, life-threatening.
It’s important to bring awareness to the difficult-to-treat negative symptoms of schizophrenia and the significant side effects of conventional schizophrenia medications, both of which have been largely overlooked in schizophrenia treatment.
It was encouraging to see how the researchers used a high throughput and data-driven strategy to identify new potential medications.
Finally, it was great to see clinical trial diversity highlighted since this is a huge problem, not only in psychopharmacology research, but in clinical research more generally.