Mental illness and drug development

Abstract

Mental illnesses are among the most incapacitating of all diseases. For decades, effective, well-documented drugs have been accessible. However, a lack of knowledge about the pathophysiology of mental disorders has impeded the development of new treatments. Drug research must shift to a net* mechanism-based paradigm, utilizing modern genetic and molecular medicine technologies. At the same time, this new paradigm must be accompanied by a similar commitment to upgrading existing clinical trial methodologies.

Traditional disease burden measurements like prevalence and mortality have greatly understated mental diseases’ psychological, societal, and economic costs, which are typically debilitating rather than fatal. The “disability-adjusted life year” (DALY) is defined as healthy years of life lost due to early mortality or (ii) disability, according to the highly recognized World Health Organization (WHO)World Bank assessment on the Global Burden of Disease1. Depression ranks second only to heart disease as a source of DALYs in established market economies and fourth overall. 2 As a result of this high level of burden, awareness of the need for therapies and, eventually, tested measures for prevention has grown.

Methodologies for drug discovery

The textbook approach to drug discovery follows a logical sequence from the bench to the bedside to the clinic to the community: basic research defines molecular targets; biochemical assays screen for lead compounds; animal studies establish pharmacokinetic and pharmacodynamic parameters, and toxicology studies assess safety and risk. This leads to human clinical trials in a well-documented multiphased development process. The textbook approach has not characterized drug discovery in mental health, despite its widespread acceptance as the ideal for fundamental, translational, and clinical research. Rather, there have been three major models of discovery.

The normal pattern for drug development is luck or the unintentional finding of therapeutic benefits. Charpentier, for example, produced chlorpromazine in the early 1950s at Rhone-Poulenc. Henri Laborit, a surgeon, used the substance to induce “artificial hibernation” and predicted its potential for application in psychiatry in 1952. Benefits were discovered in single cases and as monotherapy in open case series of patients with bipolar disease and psychosis. The drug’s research spread to other countries, and the first controlled study was conducted in England in 1954 and published.

Gaps in the process of discovery

Even though the lucky, nonlinear method of drug discovery has resulted in several significant and even revolutionary improvements in our approaches to the care of persons with mental illnesses, our therapeutic arsenal has critical gaps.

The most crippling of conditions, heart disease, has at least 15 different pharmacological classes available for treatment, most of which were created in the recent few decades. We only know a few monoamine-elevating methods of monoamine oxidase inhibition, serotonin, or norepinephrine uptake inhibitors in depression. Even fewer techniques in schizophrenia are classified as dopamine receptor antagonists or a combination of various effects (atypicals). Lithium, anticonvulsants, and atypical antipsychotics are the three medications used to treat bipolar disorder.

Following the discovery of a medication

The first modern randomized controlled trial, the Medical Research Council (MRC) trial of streptomycin, developed the procedures we use to research medications in human clinical trials for the most part in the 1940s and 1950s.

Despite this, practically everything we do in clinical trials for depression reduces treatment response, increases placebo response, and inflates the efficacy of active psychosocial comparators in combination treatment approaches. Numerous things have a role in this.

Patients are chosen.

Patients who are suicidal or psychotic or have a range of common comorbidities, such as physical illness, substance misuse, or personality problem, are frequently excluded from subject selection by filtering the severity distribution through admission criteria.

Investigate the operations

Recruitment is sometimes set up as a horse race in large, multi-site studies, with enrollment ending when the whole research sample is reached. The majority of payments to sites are made on a per-patient basis.

Measures of success

There is a trend in psychiatry studies in general, and depression trials in particular, of employing too many measures, the majority of which are rating scales or self-report forms with doubtful validity and known unreliability.

Analysis

The most common statistical methods for analyzing trial data, such as “intent to treat” or “last observation carried forward,” may favor a placebo response.

Conclusion

Clinical studies frequently fail because we feel compelled to follow traditional clinical trial methodologies. New science and therapies should be subjected to an acceptable technique based on the most up-to-date available information. The usual methods for clinical trials in mental diseases need to be re-engineered urgently.

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