Evidence- and consensus-based guidelines for drug-drug interactions with anticancer drugs:A practical and universal tool for management

Drug-drug interactions (DDIs) with anticancer drugs are common and can significantly affect efficacy and toxicity of treatment. Therefore, a Dutch Multidisciplinary Expert group is assessing the clinical signifi-cance of DDIs in oncology and provides recommendations for the management of these DDIs. We present an overview of methodology and outcome of an evidence-and consensus-based assessment of DDIs be-tween anticancer drugs and non-anticancer drugs.A literature search was performed through PubMed and EMA and FDA assessment reports, to iden-tify potential DDI's involving anticancer drugs. For each potential DDI a concept report for risk analysis and practical advice for management was created. Subsequently, this risk analysis and the corresponding advice were assessed and weighed.A total of 290 potential DDIs have been identified in the literature thus far. Of these 290 potential DDIs, the Expert Group has identified 94 (32%) DDIs as clinically relevant, with a need for an automated alert and a suggested intervention. Furthermore, 110 DDIs have been identified as clinically not relevant. For 86 potential DDIs evidence supporting a relevant DDI was insufficient and in these cases neither an alert nor advice regarding a suggested intervention were formulated.A transparent risk analysis is presented for identification of clinically relevant DDIs with anticancer drugs. Integration of DDI guidelines into the national electronic prescribing system is essential to achieve optimal efficacy and minimal toxicity in patients receiving anticancer therapy. A clear overview of clin-ically relevant DDIs with anticancer therapy provides clinicians with a structured, evidence-based and consensus-built tool for anticancer therapy surveillance. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Personalised Therapeutic

Improving medication adherence in diabetes type 2 patients through Real Time Medication Monitoring: a Randomised Controlled Trial to evaluate the effect of monitoring patients' medication use combined with short message service (SMS) reminders

Contains fulltext : 97026.pdf (publisher's version ) (Open Access)BACKGROUND: Innovative approaches are needed to support patients' adherence to drug therapy. The Real Time Medication Monitoring (RTMM) system offers real time monitoring of patients' medication use combined with short message service (SMS) reminders if patients forget to take their medication. This combination of monitoring and tailored reminders provides opportunities to improve adherence. This article describes the design of an intervention study aimed at evaluating the effect of RTMM on adherence to oral antidiabetics. METHODS/DESIGN: Randomised Controlled Trial (RCT) with two intervention arms and one control arm involving diabetes type 2 patients with suboptimal levels of adherence to oral antidiabetics (less than 80% based on pharmacy refill data). Patients in the first intervention arm use RTMM including SMS reminders and a personal webpage where they can monitor their medication use. Patients in the second intervention arm use RTMM without SMS reminders or webpage access. Patients in the control arm are not exposed to any intervention. Patients are randomly assigned to one of the three arms. The intervention lasts for six months. Pharmacy refill data of all patients are available from 11 months before, until 11 months after the start of the intervention. Primary outcome measure is adherence to oral antidiabetics calculated from: 1) data collected with RTMM, as a percentage of medication taken as prescribed, and as percentage of medication taken within the correct time interval, 2) refill data, taking the number of days for which oral antidiabetics are dispensed during the study period divided by the total number of days of the study period. Differences in adherence between the intervention groups and control group are studied using refill data. Differences in adherence between the two intervention groups are studied using RTMM data. DISCUSSION: The intervention described in this article consists of providing RTMM to patients with suboptimal adherence levels. This system combines real time monitoring of medication use with SMS reminders if medication is forgotten. If RTMM proves to be effective, it can be considered for use in various patient populations to support patients with their medication use and improve their adherence. TRIAL REGISTRATION: Netherlands Trial Register NTR1882

A Semantic Approach to Protocold using Process Algebra

We study of the operational behaviour of the specification language Protocold. We examine whether BPA(+) (Basic Process Algebra with backtracking) forms a useful basis for a clear representation of the execution of certain language constructs from Protocold. Our primary focus is on those constructs that contain some form of backtracking. Backtracking in Protocold contains the undoing of bindings of object names (logical variables). We first provide a short introduction to both formalisms, and then make a rough comparison of them both. Some elementary Protocold features, such as object names and the binding of object names, are then defined relative to a special data environment for BPA(+). Finally, a small language PCL is defined for the description of the operational behaviour of Protocold-like expressions, as well as a mapping from \Sigma(PC L) expressions to \Sigma(BPA(+)) terms. Some operational equivalences that hold in Protocold are defined as rules in PCL , such that algebraic m..

EURIS: a specification method for distributed interlockings

Safety systems for railways have shifted from electronic relays to more computer-oriented approaches. This article highlights the language EURIS from NS Railinfrabeheer, which champions an object-oriented method for the specification of interlocking logics