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The aim of this study was to develop and to validate a toxicological untargeted screening relying on LC-HRMS in meconium including the detection of the four main classes of drugs of abuse (DoA; amphetamines, cannabinoids, opioids and cocaine). The method was then applied to 29 real samples. Analyses were performed with a liquid chromatography system coupled to a benchtop Orbitrap operating in a data-dependent analysis. The sample amount was 300 mg of meconium extracted twice by solid phase extraction following two distinct procedures. Raw data were processed using the Compound Discoverer 3.2 software (Thermo). The method was evaluated and validated on 15 compounds (6-MAM, morphine, buprenorphine, norbuprenorphine, methadone, EDDP, amphetamine, MDA, MDMA, methamphetamine, cocaine, benzoylecgonine, THC, 11-OH-THC, THC-COOH). Limits of detection were between 0.5 and 5 pg/mg and limits of identification between 5 and 50 pg/mg. Mean matrix effect was between −79 and −19% (n = 6) and mean overall recovery between 18 and 73% (n = 6) at 100 pg/mg. The application allows the detection of 88 substances, including 47 pharmaceuticals and 15 pharmaceutical metabolites, cocaine and its metabolites, THC and its metabolites, and natural (morphine, codeine) and synthetic (methadone, buprenorphine, tramadol, norfentanyl) opioids. This method is now used routinely for toxicological screening in high-risk pregnancies

Background: Different liquid chromatography tandem mass spectrometry (LC–MS/MS) methods have been published for quantification of monoclonal antibodies (mAbs) in plasma but thus far none allowed the simultaneous quantification of several mAbs, including immune checkpoint inhibitors. We developed and validated an original multiplex LC–MS/MS method using a ready-to-use kit to simultaneously assay 7 mAbs (i.e., bevacizumab, cetuximab, ipilimumab, nivolumab, pembrolizumab, rituximab and trastuzumab) in plasma. This method was next cross-validated with respective reference methods (ELISA or LC–MS/MS). Methods: The mAbXmise kit was used for mAb extraction and full-length stable-isotope-labeled antibodies as internal standards. The LC–MS/MS method was fully validated following current EMA guidelines. Each cross validation between reference methods and ours included 16–28 plasma samples from cancer patients. Results: The method was linear from 2 to 100 µg/mL for all mAbs. Inter- and intra-assay precision was

Different target exposures with sunitinib have been proposed in metastatic renal cell carcinoma (mRCC) patients, such as trough concentrations or AUCs. However, most of the time, rather than therapeutic drug monitoring (TDM), clinical evidence is preferred to tailor dosing, i.e., by reducing the dose when treatment-related toxicities show, or increasing dosing if no signs of efficacy are observed. Here, we compared such empirical dose adjustment of sunitinib in mRCC patients, with the parallel dosing proposals of a PK/PD model with TDM support. In 31 evaluable patients treated with sunitinib, 53.8% had an empirical change in dosing after treatment started (i.e., 46.2% decrease in dosing, 7.6% increase in dosing). Clinical benefit was observed in 54.1% patients, including 8.3% with complete response. Overall, 58.1% of patients experienced treatment discontinuation eventually, either because of toxicities or progressive disease. When choosing 50–100 ng/mL trough concentrations as a target exposure (i.e., sunitinib + active metabolite N-desethyl sunitinib), 45% patients were adequately exposed. When considering 1200–2150 ng/mL.h as a target AUC (i.e., sunitinib + active metabolite N-desethyl sunitinib), only 26% patients were in the desired therapeutic window. TDM with retrospective PK/PD modeling would have suggested decreasing sunitinib dosing in a much larger number of patients as compared with empirical dose adjustment. Indeed, when using target trough concentrations, the model proposed reducing dosing for 61% patients, and up to 84% patients based upon target AUC. Conversely, the model proposed increasing dosing in 9.7% of patients when using target trough concentrations and in 6.5% patients when using target AUC. Overall, TDM with adaptive dosing would have led to tailoring sunitinib dosing in a larger number of patients (i.e., 53.8% vs. 71–91%, depending on the chosen metrics for target exposure) than a clinical-based decision. Interestingly, sunitinib dosing was empirically reduced in 41% patients who displayed early-onset severe toxicities, whereas model-based recommendations would have immediately proposed to reduce dosing in more than 80% of those patients. This observation suggests that early treatment-related toxicities could have been partly avoided using prospective PK/PD modeling with adaptive dosing. Conversely, the possible impact of model-based adapted dosing on efficacy could not be fully evaluated because no clear relationship was found between baseline exposure levels and sunitinib efficacy measured at 3 months.