Background: Side effects of antipsychotic drugs play a key role in non-adherence and discontinuation of treatment in schizophrenia spectrum disorders (SSD). Precision medicine aims to minimize such side effects by selecting the right treatment for the right patient. However, to determine the extent of precision medicine that is required, we need to (1) show that there is indeed variation in side effects and (2) estimate the amount of variation in those side effects between patients. While clinical observations suggest that such variation may be considerable, a statistical comparison of side effect variation between active and control treatments is required to confirm this. Here, we hypothesized to find larger side effect variation in treatment compared with control in patients treated with first and second generation antipsychotics. Methods: We included double-blind, placebo-controlled, randomized controlled trials (RCTs) of adults with a diagnosis of SSD and prescription for licensed antipsychotic drugs. Standard deviations of the pre-post treatment differences of weight gain, prolactin levels,and corrected QT (QTc) times were extracted. Data quality and validity were ensured by following the PRISMA guidelines. The outcome measure was the overall variability ratio of treatment to control across RCTs. Individual variability ratios were weighted by the inverse-variance method and entered into a random-effects model. Results: We included N = 16578 patients for weight gain, N = 16633 patients for prolactin levels, and N = 10384 patients for QTc time. Variability ratios (VR) were significantly increased for weight gain (VR = 1.08; 95% CI: 1.02 - 1.14; P = 0.004) and prolactin levels (VR = 1.38; 95% CI: 1.17 - 1.62; P < 0.001) but did not reach significance for QTc time (VR = 1.05; 95% CI: 0.98 - 1.12; P = 0.135). Conclusion: We found increased variability in major side effects in patients with SSD under treatment with second generation antipsychotics, suggesting that subgroups of patients or even individual patients may benefit from improved treatment allocation through stratified or personalized medicine, respectively.