Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.

BACKGROUND: Autistic spectrum disorders (ASD) are severe neurodevelopmental alterations characterised by deficits in social communication and repetitive and restricted behaviours. About a third of patients receive pharmacological treatment for comorbid symptoms. However, 30–50% do not respond adequately and/or present severe and long-lasting side effects. METHODS: Genetic variants in CYP1A2, CYP2C19, CYP2D6 and SLC6A4 were investigated in N = 42 ASD sufferers resistant to pharmacological treatment. Clinical recommendations based on their pharmacogenetic profiles were provided within 24–48 h of receiving a biological sample. RESULTS: A total of 39 participants (93%) improved after the pharmacogenetic intervention according to their CGI scores (difference in basal-final scores: 2.26, SD 1.55) and 37 participants (88%) according to their CGAS scores (average improvement of 20.29, SD 11.85). Twenty-three of them (55%) achieved symptom stability (CGI ≤ 3 and CGAS improvement ≥ 20 points), requiring less frequent visits to their clinicians and hospital stays. Furthermore, the clinical improvement was higher than that observed in a control group (N = 62) with no pharmacogenetic interventions, in which 66% responded to treatment (difference in CGI scores: −0.87, SD 9.4, p = 1 × 10⁻⁵; difference in CGAS scores: 6.59, SD 7.76, p = 5 × 10⁻⁸). CONCLUSIONS: The implementation of pharmacogenetic interventions has the potential to significantly improve the clinical outcomes in severe comorbid ASD populations with drug treatment resistance and poor prognosis.