BLUPRINTRx® KNOWLEDGE CENTER
Scientific & Clinical Evidence
Peer-reviewed and scientific resources supporting phenoconversion, functional pharmacokinetics, drug exposure, DDGI, polypharmacy and medication-risk context.
Research Study Evidence Matrix
The controlled Evidence Matrix is presented directly below as the website's study-level evidence library. E01–E20 remain the stable evidence IDs. Use the filters or search to explore the evidence without downloading a spreadsheet.
| ID | Year | Publication / Study Type | Evidence Area / Population | Key Finding | Strength | Claim Boundary | Source |
|---|---|---|---|---|---|---|---|
| E01 | 2026 | Scodellaro S, Triantafilou S, Cohn I. Factors Influencing Phenoconversion in CYP-Mediated Drug Metabolism: A Scoping Review. Scoping review (43 studies) | Phenoconversion & Functional PK CYP2D6, CYP2C19, CYP3A4; multiple populations | Phenoconversion is multifactorial; reported contributors include DDIs/DDGIs, inflammation, pregnancy, age-related changes and smoking. | CORE | Supports underlying pharmacology, not validation of TruTYPE algorithm or a specific exposure/risk score. | View source → |
| E02 PREPRINT | 2026 | Stingl J, Molden E, Hole K, Wollmann BM, Viviani R. Pharmacogenetic phenoconversion modeling of DDGIs on CYP2C19 activity: effects of comedication by genotype on escitalopram concentrations. Real-world TDM modeling; preprint; n=2,852 | Drug Exposure & Quantitative PK CYP2C19; escitalopram; psychiatric TDM | Quantitative model integrates genotype and multiple co-medications to estimate CYP2C19 phenoconversion in real-world TDM data. | EMERGING / HIGH CONCEPTUAL | PREPRINT / not peer reviewed. Does not validate TruTYPE/TruRISK or clinical outcome prediction. | View source → |
| E03 | 2025 | Sarömba JA, Müller JP, Tupiec J, et al. Solanidine-derived CYP2D6 phenotyping elucidates phenoconversion in multimedicated geriatric patients. Clinical phenotyping study; n=88 | Polypharmacy & Older Adults CYP2D6; geriatric multimorbidity; median 15 medications | Diet-derived biomarkers measured CYP2D6 activity; each additional CYP2D6 substrate/inhibitor was associated with lower expected activity score in patients with functional variants. | CORE | Measured CYP activity biomarker is not the same as measuring every substrate's plasma concentration or clinical outcome. | View source → |
| E04 | 2024 | De Brabander EY, et al. Clinical effects of CYP2D6 phenoconversion in patients with psychosis. Clinical cohort / phenotype correction | Validation & Scientific Boundaries CYP2D6; psychosis; inhibitor-adjusted phenotype | Applying inhibitor-related phenoconversion materially increased poor-metabolizer classification; clinical outcome associations were not robust. | CORE — VALIDATION/LIMITATIONS | Phenotype correction does not automatically establish outcome prediction. | View source → |
| E05 | 2024 | Aly SM, Hennart B, Gaulier J-M, Allorge D. Effect of CYP2D6, 2C19, and 3A4 Phenoconversion in Drug-Related Deaths. Forensic toxicogenetic study | Medication Safety & Exposure CYP2D6, CYP2C19, CYP3A4; drug-related deaths | Examines genotype, co-medications/phenoconversion and toxicological findings in drug-related deaths. | SPECIALIZED | Must not imply TruRISK predicts mortality or causation. | View source → |
| E06 | 2024 | Abouir K, Exquis N, Gloor Y, Daali Y, Samer CF. Phenoconversion Due to Drug-Drug Interactions in CYP2C19 Genotyped Healthy Volunteers. Prospective exploratory clinical study | Phenoconversion & Functional PK CYP2C19; healthy volunteers; omeprazole probe + fluvoxamine/voriconazole | Phenoconversion occurred in >80% of volunteers; measured phenotype shifted substantially after CYP2C19 inhibitor exposure. | CORE | Healthy-volunteer probe study; do not generalize magnitude to all drugs/patients. | View source → |
| E07 | 2026 | Krebs K, et al. Pharmacokinetic recall study of Estonian Biobank participants with novel genetic variants in CYP2C19 and CYP2D6. Pharmacokinetic recall / biobank study | Phenoconversion & Functional PK CYP2C19, CYP2D6; genotype-phenotype discordance; inhibitor exposure | Metabolic-activity outliers inconsistent with genotype were identified; inhibitor exposure in some outliers supported DDI-related phenoconversion. | CORE / RECENT | Update citation when final version replaces early-access/article-in-press version. | View source → |
| E08 | 2023 | de Jong LM, et al. The impact of CYP2C19 genotype on phenoconversion by concomitant medication. Human liver microsome experimental study | Drug–Drug–Gene Interactions CYP2C19; genotype groups; multiple inhibitors | Measured CYP2C19 activity showed substantial genotype-phenotype discordance; inhibitor effects and phenotypic switches differed by basal activity/genotype. | CORE MECHANISTIC | In-vitro microsome study; clinical magnitude should not be assumed identical in vivo. | View source → |
| E09 | 2020 | Malki MA, Pearson ER. Drug-drug-gene interactions and adverse drug reactions. Review / conceptual classification | Drug–Drug–Gene Interactions CYP2C9, CYP2C19, CYP2D6 and DDGI examples | Classifies inhibitory, induction and phenoconversion DDGIs and explains how genetic variation plus perpetrator drugs can markedly alter concentrations. | FOUNDATIONAL | Foundational review, not validation of a proprietary patient-specific risk score. | View source → |
| E10 | 2020 | Klomp SD, Manson ML, Guchelaar H-J, Swen JJ. Phenoconversion of Cytochrome P450 Metabolism: A Systematic Review. Systematic review; 27 studies | Validation & Scientific Boundaries CYP phenoconversion; medications, age, cancer, inflammation, smoking and other factors | Lower-metabolizer shifts were reported with inhibitors, age, cancer and inflammation; higher-metabolizer shifts with inducers/smoking; clinical effectiveness/toxicity impact remained uncertain. | FOUNDATIONAL / LIMITATION | Explicitly states clinical effectiveness/toxicity consequences remain unclear. | View source → |
| E11 | 2026 | Porrogi P. Dynamic phenotype monitoring to prevent genotype–phenotype discrepancies in pharmacogenetic-guided drug therapy. Structured narrative review | Phenoconversion & Functional PK CYP enzymes + transporters; inflammation, polypharmacy, transporter dysfunction, biomarkers | Argues static PGx can diverge from functional state and proposes functional biomarker monitoring for dynamic phenotype assessment. | RECENT / CONCEPTUAL | Narrative/structured review with proposed non-validated biomarker frameworks; do not present proposed monitoring index as validated. | View source → |
| E12 | 2022 | Drug metabolic enzyme genotype-phenotype discrepancy: High phenoconversion rate in patients treated with antidepressants. Clinical phenotyping study | Phenoconversion & Functional PK Antidepressant-treated patients; CYP2D6, CYP2C19, CYP2C9 | Reports reduced CYP metabolic capacity and a high rate of genotype–phenotype discrepancy/phenoconversion in antidepressant-treated patients. | CORE CLINICAL | Do not infer a specific toxicity probability from phenoconversion prevalence alone. | View source → |
| E13 | 2013 | In vivo quantitative prediction of the effect of gene polymorphisms and drug interactions on drug exposure for CYP2C19 substrates. Quantitative PK modeling using 60 studies | Drug Exposure & Quantitative PK CYP2C19; 25 substrates; 5 genotype variants; 10 inhibitors | Unified quantitative approach used genotype and DDI data to predict altered in-vivo AUC ratios for CYP2C19 substrates. | FOUNDATIONAL QUANTITATIVE | Older foundational model; does not validate current TruTYPE implementation or TruRISK outcomes. | View source → |
| E14 | 2021 | Cicali EJ, et al. How to Integrate CYP2D6 Phenoconversion into Clinical Pharmacogenetics: A Tutorial. Clinical implementation tutorial | Phenoconversion & Functional PK CYP2D6; inhibitor-adjusted activity scores; clinical PGx | Describes a standardized clinical method for adjusting CYP2D6 activity scores for strong/moderate inhibitors and integrating phenoconversion into practice. | FOUNDATIONAL IMPLEMENTATION | A tutorial/calculator framework is not validation of TruTYPE's proprietary multi-pathway algorithm. | View source → |
| E15 | 2026 | Laureano-Rivera M, et al. Genetic and epigenetic determinants of cytochrome P450 activity in psychopharmacology: from pharmacogenetics to functional pharmacogenomics. Review | Phenoconversion & Functional PK Psychopharmacology; CYP activity; epigenetic/environmental modulation | Recent review emphasizes that genotype incompletely predicts psychiatric drug response and frames metabolic capacity as a dynamic functional state influenced by regulatory/environmental factors. | RECENT REVIEW | Not a free-reuse resource; use citation/link only and avoid reproducing publisher figures/text. | View source → |
| E16 | 2023 | den Uil MG, Hut HW, Wagelaar KR, et al. Pharmacogenetics and phenoconversion: the influence on side effects experienced by psychiatric patients. Retrospective clinical cohort; n=117 | Exposure → Clinical Risk Bridge CYP2C19/CYP2D6; psychiatric outpatients; plasma drug levels | Phenoconversion occurred in CYP2C19 and CYP2D6; CYP2D6 IM/PM groups had higher concentration-dose ratios. Specific side-effect associations were reported, while total UKU side-effect score was not significantly associated with phenotype. | CORE CLINICAL BRIDGE | Small retrospective cohort; several analyses underpowered; overall UKU score was not significantly associated. Specific associations must not be generalized. | View source → |
| E17 | 2024 | Case report: Therapeutic drug monitoring and CYP2D6 phenoconversion in a protracted paroxetine intoxication. Case report | Exposure → Clinical Risk Bridge CYP2D6; paroxetine; chronic therapy + overdose | A genotype-predicted intermediate metabolizer experienced a toxic paroxetine plasma level with delirium persisting for about one month; authors suggest phenoconversion to very low CYP2D6 activity contributed. | SUPPORTIVE CASE EVIDENCE | Single overdose case; cannot establish population-level risk or causality and should not be used as validation of TruRISK. | View source → |
| E18 | 2015 | de Leon J. Phenoconversion and therapeutic drug monitoring. Clinical pharmacology commentary with TDM examples | Drug Exposure & Quantitative PK CYP2D6/CYP2C19; venlafaxine, risperidone, clobazam, clozapine | Describes TDM signatures of phenoconversion. In risperidone data, CYP2D6 inhibitor use strongly increased inverted parent/metabolite ratios; genotype modified the frequency of phenoconversion. | FOUNDATIONAL TDM | Commentary synthesizes examples; some underlying risperidone RCT TDM data were not peer-reviewed. Use as supporting, not primary, evidence. | View source → |
| E19 | 2014 | Shah RR, Smith RL. Addressing phenoconversion: the Achilles' heel of personalized medicine. Comprehensive review | Exposure → Clinical Risk Bridge CYP phenoconversion; multiple substrates/inhibitors | Review compiles substantial AUC increases for CYP2D6 substrates under inhibitor-driven phenoconversion and explains that PK changes may affect safety/efficacy depending on pharmacology and therapeutic index. | FOUNDATIONAL QUANTITATIVE | Review compiles heterogeneous studies; AUC effects are drug-specific and should not be generalized across substrates. | View source → |
| E20 | 2021 | Hahn M, Roll SC. The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug-Drug Interactions: Drug-Gene, Drug-Gene-Gene and Drug-Drug-Gene Interactions. Review | Exposure → Clinical Risk Bridge DDI/DGI/DDGI; CYP and UGT; toxicity/ineffectiveness | Review explains that not every DDI causes an adverse event and that genetic profile and phenoconversion can modify the clinical relevance of PK interactions, including toxicity or ineffectiveness. | FOUNDATIONAL RISK FRAMEWORK | Review supports the framework, not an absolute patient-specific event probability or proprietary TruRISK score. | View source → |
Scientific boundary: The matrix summarizes published evidence relevant to functional pharmacokinetics and medication-risk context. It does not establish independent validation of TruTYPE® or TruRISK®, and evidence limitations shown for each study should be considered when interpreting relevance.