The study introduces a standardized method for comparing dosages of different antipsychotic medications, which is crucial for designing clinical trials and examining long-term medication side effects. The method involves creating dose equivalents by comparing each drug to chlorpromazine and haloperidol using regression analysis. The resulting formulas are used to derive new chlorpromazine and haloperidol equivalents, which are then incorporated into a dose-year formula to measure cumulative drug exposure over time. The dose-year formula is defined as the product of the dose of a particular antipsychotic (converted into equivalents of chlorpromazine or haloperidol) and the time on that dose expressed in years. The study finds that the derived dose equivalents are highly linear, with $R^2$ values greater than 0.9, and that a power transformation further improves linearity. The method allows for the comparison of different drugs in clinical trials and provides a quantitative measure of long-term medication exposure, which can be useful for studying the relationship between long-term treatment and side effects. The study also discusses the limitations of the method, including the potential for small errors in initial conversion factors to accumulate over time and the inability to account for interactive effects of polypharmacy.The study introduces a standardized method for comparing dosages of different antipsychotic medications, which is crucial for designing clinical trials and examining long-term medication side effects. The method involves creating dose equivalents by comparing each drug to chlorpromazine and haloperidol using regression analysis. The resulting formulas are used to derive new chlorpromazine and haloperidol equivalents, which are then incorporated into a dose-year formula to measure cumulative drug exposure over time. The dose-year formula is defined as the product of the dose of a particular antipsychotic (converted into equivalents of chlorpromazine or haloperidol) and the time on that dose expressed in years. The study finds that the derived dose equivalents are highly linear, with $R^2$ values greater than 0.9, and that a power transformation further improves linearity. The method allows for the comparison of different drugs in clinical trials and provides a quantitative measure of long-term medication exposure, which can be useful for studying the relationship between long-term treatment and side effects. The study also discusses the limitations of the method, including the potential for small errors in initial conversion factors to accumulate over time and the inability to account for interactive effects of polypharmacy.