Pharmacogenomics is a key component of personalized medicine that promises safer and more effective drug treatment by individualizing drug choice and dose based on genetic profiles. In clinical practice, genetic biomarkers are used to categorize patients into *-alleles to predict CYP450 enzyme activity and adjust drug dosages accordingly. However, this approach leaves a large part of variability in drug response unexplained. Here, we present a proof-of-concept approach that uses continuous-scale (instead of categorical) assignments to predict enzyme activity. We used full CYP2D6 gene sequences obtained with long-read amplicon-based sequencing and cytochrome P450 (CYP) 2D6–mediated tamoxifen metabolism data from a prospective study of 561 patients with breast cancer to train a neural network. The model explained 79% of interindividual variability in CYP2D6 activity compared to 54% with the conventional *-allele approach, assigned enzyme activities to known alleles with previously reported effects, and predicted the activity of previously uncharacterized combinations of variants. The results were replicated in an independent cohort of tamoxifen-treated patients (model R² adjusted = 0.66 versus *-allele R² adjusted = 0.35) and a cohort of patients treated with the CYP2D6 substrate venlafaxine (model R² adjusted = 0.64 versus *-allele R² adjusted = 0.55). Human embryonic kidney cells were used to confirm the effect of five genetic variants on metabolism of the CYP2D6 substrate bufuralol in vitro. These results demonstrate the advantage of a continuous scale and a completely phased genotype for prediction of CYP2D6 enzyme activity and could potentially enable more accurate prediction of individual drug response.

药物基因组学是个性化医疗的一个关键组成部分，它通过基于基因特征的个体化药物选择和剂量来保证更安全、更有效的药物治疗。在临床实践中，遗传生物标志物用于将患者分类为 *-等位​​基因，以预测 CYP450 酶活性并相应地调整药物剂量。然而，这种方法使药物反应的很大一部分变异性无法解释。在这里，我们提出了一种概念验证方法，该方法使用连续规模（而不是分类）分配来预测酶活性。我们使用了完整的CYP2D6使用基于长读长扩增子的测序和细胞色素 P450 (CYP) 2D6 介导的他莫昔芬代谢数据获得的基因序列来自对 561 名乳腺癌患者的前瞻性研究，以训练神经网络。该模型解释了 CYP2D6 活性的 79% 的个体间变异性，而传统的 *-等位​​基因方法为 54%，将酶活性分配给具有先前报告效应的已知等位基因，并预测了先前未表征的变体组合的活性。结果在他莫昔芬治疗的独立队列（调整后的模型R ² = 0.66 与调整后的 *-等位​​基因R ² = 0.35）和用 CYP2D6 底物文拉法辛治疗的患者队列（模型R ²调整后 = 0.64，而 *-等位​​基因R ²调整后 = 0.55）。人类胚胎肾细胞用于确认五种遗传变异对体外 CYP2D6 底物布法洛尔代谢的影响。这些结果证明了连续规模和完全定相基因型在预测 CYP2D6 酶活性方面的优势，并有可能更准确地预测个体药物反应。