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4CPS-241 DDI-predictor: a novel clinical pharmacy decision-making tool for dose adaptation?
  1. F Moreau1,
  2. N Simon1,2,
  3. M Tod3,4,
  4. B Decaudin1,2,
  5. P Odou1,2
  1. 1CHU Lille, institut de pharmacie, lille, france
  2. 2Univ. Lille, EA 7365 – Grita – Groupe de Recherche sur les Formes Injectables et les Technologies Associées, Lille, France
  3. 3Université Lyon 1- Faculté de Médicine Lyon-Sud-Charles Mérieux, Emr 3738, Oullins, France
  4. 4Groupement Hospitalier Nord- Hospices Civils de Lyon, Pharmacy, Lyon, France


Background To date, pharmacists have been limited to advising physicians about changes in drug prescriptions in the case of drug-drug interactions (DDI), cirrhosis or the presence of genetic polymorphism on P450 cytochromes (CYP). Dose adaptation is complicated. DDI-Predictor (DDI-P) is a free online application composed of five modules. Three modules are: drug-drug interaction; drug exposure level in case of cirrhosis; and drug exposure level in case of genetic polymorphism for CYP2D6, 2 C9 and 2 C19. The other two modules are combinations of the previous three modules, namely (a)+(b) or (a)+(c).

Purpose To describe DDI-P use as a clinical pharmacy decision-making tool.

Material and methods Eighteen clinical pharmacists were trained before using DDI-P. DDI-P computed a ratio of area under the drug-concentration curves (RAUC) by comparing an AUC to a standard. Dose adaptation was calculated from RAUC. Pharmaceutical intervention (PI) was advised if 0.5≤RAUC (induction) or RAUC ≥1.5 (inhibition). Data recorded in a standardised datasheet in Excel software (Microsoft, France) were: date, drug and posology, interacting drug, cirrhosis grade, module used, RAUC, PI and medical acceptation (MA). Data were analysed by one referent pharmacist. The endpoints were pharmaceutical intervention and medical acceptation rates.

Results 1 99 733 prescriptions were analysed during 26 months and 290 cases involved DDI-P. Seventy-seven cases were excluded (infructuous research, n=43; application misuse, n=30; uninterpretable results, n=4). Other cases concerned DDI with inducers (n=56; 26%) or inhibitors (n=145; 68%) and cirrhotic patients (n=12). PI occurred in 121 cases (56.8%), for inducers (75%), for inhibitors (54%) and for cirrhosis (66%). For inducers with 0.5≤RAUC, PI concerned: drug switch (33%) and interactor stop (6%). For inhibitors with RAUC ≥1.5, PI were dose-lowering (17/79) or drug switch (7/79). The MA rates were 88% and 82% for inducers and inhibitors, and 100% for cirrhosis, respectively.

Conclusion This first study assessing DDI-P shows how it may help clinical pharmacists in their daily practice. RAUC value leads pharmacists to assess the importance of DDI and to propose therapeutic adjustments to physicians, contributing to therapeutic decisions. Although it is easy to use, pharmacists must therefore be trained to interpret the result in the clinical context at the time of the analysis to avoid potential misuses.

References and/or acknowledgements No conflict of interest.

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