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The use of monoclonal antibodies (mAbs) in the clinic has successfully expanded to treatment of cancer, viral infections, inflammations, and other indications. However, some of the classes of mAbs that are used in the clinic show the formation of anti-drug antibodies (ADAs) leading to loss of efficacy. This review describes ADA formation for the various mAbs, and its clinical effect. Lastly, this review considers the use of HLA-haplotypes as biomarkers to predict vulnerability of patients sensitive to formation of ADAs.

Translating CYP2D6 genotype to metabolizer phenotype is not standardized across clinical laboratories offering pharmacogenetic (PGx) testing and PGx clinical practice guidelines, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). The genotype to phenotype translation discordance between laboratories and guidelines can cause discordant cytochrome P450 2D6 (CYP2D6) phenotype assignments and, thus lead to inconsistent therapeutic recommendations and confusion among patients and clinicians. A modified‐Delphi method was used to obtain consensus for a uniform system for translating CYP2D6 genotype to phenotype among a panel of international CYP2D6 experts. Experts with diverse involvement in CYP2D6 interpretation (clinicians, researchers, genetic testing laboratorians, and PGx implementers; n = 37) participated in conference calls and surveys. After completion of 7 surveys, a consensus (> 70%) was reached with 82% of the CYP2D6 experts agreeing to the final CYP2D6 genotype to phenotype translation method. Broad adoption of the proposed CYP2D6 genotype to phenotype translation method by guideline developers, such as CPIC and DPWG, and clinical laboratories as well as researchers will result in more consistent interpretation of CYP2D6 genotype.

Pre‐therapeutic UGT1A1 genotyping is increasingly performed in patients receiving irinotecan, as its active metabolite SN‐38 is primarily cleared through UGT1A1‐mediated glucuronidation. Patients with the UGT1A1*28/*28 genotype exhibit reduced UGT1A1 activity, leading to increased SN‐38 exposure and a higher risk of adverse events such as neutropenia and diarrhea. Although sacituzumab govitecan contains the same active metabolite as irinotecan, routine UGT1A1 genotyping prior to treatment with this drug is not yet standard practice and is not included in its product information. The aim of this study was to assess whether pre‐therapeutic UGT1A1 genotyping may also benefit patients with hormone receptor‐positive, human epidermal growth factor receptor 2‐negative and triple‐negative breast cancer who are treated with sacituzumab govitecan. A literature search was conducted to identify relevant studies assessing the impact of UGT1A1 genotyping on the safety and efficacy of sacituzumab govitecan treatment. A meta‐analysis was performed on selected studies. Additionally, a pharmacological analysis was performed using public data comparing SN‐38 levels in patients treated with sacituzumab govitecan to those receiving irinotecan. The meta‐analysis shows that grade ≥ 3 adverse events, including neutropenia, febrile neutropenia, and diarrhea, occurred more frequently in patients with the *28/*28 genotype. Furthermore, a statistically significant increased risk was found for developing grade ≥ 3 diarrhea or febrile neutropenia in this group. Although the meta‐analysis was underpowered due to small sample sizes, the pharmacological analysis demonstrated higher SN‐38 levels in patients treated with sacituzumab govitecan, supporting the rationale for UGT1A1 genotyping in this context. Study Highlights What is the current knowledge on the topic? ○Pre‐therapeutic UGT1A1 genotyping is standard practice for patients receiving irinotecan, as reduced UGT1A1 activity in individuals with the 28/28 genotype can result in increased SN‐38 exposure and a higher risk of severe toxicity. ○Although sacituzumab govitecan contains the same active metabolite, genotyping is not routinely performed before treatment and is also not mentioned in the product information. What question did this study address? ○This study investigated whether UGT1A1 genotyping may be beneficial for patients with hormone receptor‐positive, human epidermal growth factor receptor 2‐negative, or triple‐negative breast cancer who are treated with sacituzumab govitecan. What does this study add to our knowledge? ○This study provides the first combined analysis of clinical and pharmacological data supporting the relevance of UGT1A1 genotyping prior to sacituzumab govitecan treatment. ○It demonstrates that patients with the 28/28 genotype are at significantly higher risk of severe toxicity and shows that SN‐38 exposure in sacituzumab govitecan therapy may be even higher than with irinotecan. How might this change clinical pharmacology or translational science? ○These findings support the clinical relevance of UGT1A1 genotyping prior to sacituzumab govitecan therapy. ○By identifying patients with the *28/*28 genotype before treatment, clinicians can adjust dosing or enhance monitoring to reduce toxicity.

Despite advances in the field of pharmacogenetics (PGx), clinical acceptance has remained limited. The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the starting dose optimization of three anti-cancer drugs (fluoropyrimidines: 5-fluorouracil, capecitabine and tegafur) to decrease the risk of severe, potentially fatal, toxicity (such as diarrhoea, hand-foot syndrome, mucositis or myelosuppression). Dihydropyrimidine dehydrogenase (DPD, encoded by the DPYD gene) enzyme deficiency increases risk of fluoropyrimidine-induced toxicity. The DPYD-gene activity score, determined by four DPYD variants, predicts DPD activity and can be used to optimize an individual’s starting dose. The gene activity score ranges from 0 (no DPD activity) to 2 (normal DPD activity). In case it is not possible to calculate the gene activity score based on DPYD genotype, we recommend to determine the DPD activity and adjust the initial dose based on available data. For patients initiating 5-fluorouracil or capecitabine: subjects with a gene activity score of 0 are recommended to avoid systemic and cutaneous 5-fluorouracil or capecitabine; subjects with a gene activity score of 1 or 1.5 are recommended to initiate therapy with 50% the standard dose of 5-fluorouracil or capecitabine. For subjects initiating tegafur: subjects with a gene activity score of 0, 1 or 1.5 are recommended to avoid tegafur. Subjects with a gene activity score of 2 (reference) should receive a standard dose. Based on the DPWG clinical implication score, DPYD genotyping is considered “essential”, therefore directing DPYD testing prior to initiating fluoropyrimidines.

Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model‐based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model‐based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model‐based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.

Phenoconversion is the mismatch between the individual’s genotype-based prediction of drug metabolism and the true capacity to metabolize drugs due to nongenetic factors. While the concept of phenoconversion has been described in narrative reviews, no systematic review is available. A systematic review was conducted to investigate factors contributing to phenoconversion and the impact on cytochrome P450 metabolism. Twenty-seven studies met the inclusion criteria and were incorporated in this review, of which 14 demonstrate phenoconversion for a specific genotype group. Phenoconversion into a lower metabolizer phenotype was reported for concomitant use of CYP450-inhibiting drugs, increasing age, cancer, and inflammation. Phenoconversion into a higher metabolizer phenotype was reported for concomitant use of CYP450 inducers and smoking. Moreover, alcohol, pregnancy, and vitamin D exposure are factors where study data suggested phenoconversion. The studies reported genotype–phenotype discrepancies, but the impact of phenoconversion on the effectiveness and toxicity in the clinical setting remains unclear. In conclusion, phenoconversion is caused by both extrinsic factors and patient- and disease-related factors. The mechanism(s) behind and the extent to which CYP450 metabolism is affected remain unexplored. If studied more comprehensively, accounting for phenoconversion may help to improve our ability to predict the individual CYP450 metabolism and personalize drug treatment.

If the kappa for the causality analysis is calculated with the categories definite, probable, and possible in one group, which better reflects the primary endpoint, the value increases to 0·50. [...]the health-care providers’ consistency of assessments was compared between the study and control groups, again with concordant results (appendix p 17 in the Article1). Furthermore, the approach for patients in the control group was similar to the approach for patients in the study group, with participants in both groups receiving a mock safety code card. [...]we have no reasons to believe that bias played a major role. [...]by design, we applied a gatekeeping analysis, which has many advantages.3 Thus, as a first step, we analysed the effect in patients with actionable genotypes, and went onto the second step to undertake an analysis in the total population only if the first step was statistically significant. The calculated dose adjustments result in similar drug exposure, and it is the exposure that is more important than the dose. [...]in a patient with a poor CYP2D6 metabolism, the reduced dose leads to a similar drug exposure as for a patient with a typical CYP2D6 metabolism status receiving the full dose.

Purpose Due to the diversity within Europe, the implementation of pharmacogenomic testing in clinical practice faces specific challenges. In the context of the European pharmacogenomics implementation project “Ubiquitous Pharmacogenomics” (U-PGx; funded by the European Commission), we studied the current educational background. Methods We developed a questionnaire including 29 questions. It was spread out to healthcare professionals working at the future implementation sites (in Austria, Greece, Italy, Netherlands, Slovenia, Spain and Great Britain) of the U-PGx project in preparation of an educational programme. Aim of the survey was to analyse the current educational situation at the implementation sites. Results In total, 70 healthcare professionals participated in the survey. Of participants, 84.3% found pharmacogenomics relevant to their current practice, but experience was still rare. More than two-thirds (65.7%) did not order nor recommend a pharmacogenomic test in the past year. This was mainly attributed to not having enough knowledge on pharmacogenomics (40.0%). Needs were identified in application of pharmacogenomics (identifying drugs 41.4%, interpreting test results 37.2%) as well as in underlining mechanisms (better knowledge on drug metabolism 67.1%, better knowledge on basic principles of pharmacogenomics 60.0%). Conclusions This study analysed the specific attitudes, experience and education on pharmacogenomics of future users. There was a general positive attitude and interest towards pharmacogenomic testing. However, the grade of own experience, and knowledge about application and interpretation of pharmacogenomics caused uncertainty. Thus, education and training programmes may be helpful for implementation of pharmacogenomics at a homogenous level within Europe.

The use of pharmacogenomics in clinical practice is becoming standard of care. However, due to the complex genetic makeup of pharmacogenes, not all genetic variation is currently accounted for. Here, we show the utility of long-read sequencing to resolve complex pharmacogenes by analyzing a well-characterised sample. This data consists of long reads that were processed to resolve phased haploblocks. 73% of pharmacogenes were fully covered in one phased haploblock, including 9/15 genes that are 100% complex. Variant calling accuracy in the pharmacogenes was high, with 99.8% recall and 100% precision for SNVs and 98.7% precision and 98.0% recall for Indels. For the majority of gene-drug interactions in the DPWG and CPIC guidelines, the associated genes could be fully resolved (62% and 63% respectively). Together, these findings suggest that long-read sequencing data offers promising opportunities in elucidating complex pharmacogenes and haplotype phasing while maintaining accurate variant calling.

Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.