BACKGROUND AND AIMS:Rehabilitation of physical activity is an important functional outcome after endoscopic surgery. Our aim was to quantitatively assess recovery after endoscopic submucosal dissection (ESD) and transanal minimally invasive surgery (TAMIS). METHODS:In the TRIASSIC study (Netherlands Trial Registry: NL7083), patients with rectal polyps >20 mm were randomized between ESD and TAMIS. This ancillary study used smartwatches to track activity data for a 14-day preoperative baseline period and a 28-day postoperative recovery period. The primary end point for noninferiority was the mean time to recovery (≥90% of baseline step count for 2 consecutive days), assessed by means of Weibull regression with a 7-day noninferiority margin. RESULTS:Forty patients were included: 20 ESD and 20 TAMIS procedures. Median lesion size was 42.5 mm (interquartile range [IQR], 25-50), with 17.5% pT1RCs and 82.5% nonmalignant rectal polyps. Compliance with smartwatch measurements was 98.4% (IQR, 94.2-100). Within the 28-day timespan, 17 patients (85%) in the ESD group recovered and 15 (75%) in the TAMIS group (P = .43). Mean recovery times were 13.9 days for ESD and 21.0 days for TAMIS, indicating noninferiority of ESD (95% confidence interval of difference, -3.41 to 20.25). Recovery as measured by smartwatch significantly correlated with self-reported recovery (Spearman rho, 0.644; P < .001). Moderate to severe pain scores (≥4 out of 10) were reported by 15 patients (42.9%): in 27.8% of the ESD group and 58.9% of the TAMIS-group (P = .06). Increased pain scores were significantly associated with decreased physical activity (P < .01). CONCLUSIONS:In terms of mean time to physical recovery, ESD was noninferior to TAMIS. Post-procedural pain was significantly associated with reduced physical activity.

PURPOSE:Patients with cancer are prone to frequent unplanned hospital visits because of disease or treatment complications. Smartphone-based passive sensing (SBPS) comprises data collection using smartphone sensors or device usage patterns, which may be an affordable and burdenless technique for remote monitoring of patients with cancer and timely detection of safety events. The aim of this article was to systematically review the published literature to identify the current state of SBPS in oncology care and research.METHODS:A literature search was done with cutoff date July 29, 2022, using six different databases. Articles were included if they reported original studies using SBPS in patients with cancer or cancer survivors. Data extracted from studies included type of sensors used, cancer type, study objectives, and main findings.RESULTS:Twelve studies were included, the oldest report being from 2017. The most frequent of the nine analyzed sensors and smartphone analytics was the accelerometer (eight studies) and geolocation (eight studies), followed by call logs (two studies). Breast cancer was the most studied cancer type (eight studies with 111 patients), followed by GI cancers (six studies with 133 patients). All studies aiming for feasibility concluded that SBPS in oncology was feasible (seven studies). SBPS was used as a monitoring tool, with passively sensed data being correlated with adverse events, symptom burden, cancer-related fatigue, decision conflict, recovery trends after surgery, or psychosocial impact. SBPS was also used in one study as a predictive tool for health deterioration.CONCLUSION:SBPS shows early promise in oncology, although it cannot yet replace traditional tools to monitor quality of life and clinical outcomes. For this, validation of SBPS will be required. Therefore, further research is warranted with this developing technique.

The primary purpose of this study was to assess the translatability of preclinical to early clinical tolerable and pharmacologically active dose ranges for central nervous system (CNS) active drugs. As a part of this, IBs were reviewed on reporting quality. Investigator's Brochures (IBs) of studies performed at the Centre for Human Drug Research (CHDR) reporting statistically significant results of CNS activity related to the drug's mechanism of action were included. The quality of IBs was assessed based on the presence of a rationale for the chosen animal model, completeness of pharmacokinetic (PK) results in reporting and internal validity information of the preclinical evidence. The IB-derisk tool was used to generate preclinical and early clinical data overviews data. For each compound, the overlap between pharmacologically active dose ranges and well-tolerated levels was calculated for three pharmacokinetic (PK) parameters: human equivalent dose (HED), maximum plasma concentration (Cmax) and area under the curve (AUC). Twenty-five IBs were included. In general, the quality of reporting in IBs was assessed as poor. About a third of studies did not explore the entire concentration-effect curve (pre)clinically. Single dose tolerability ranges were most accurately predicted by Cmax. Human equivalent dose and AUC were the best predictors of pharmacologically active ranges. Tolerable and pharmacologically active dose ranges in healthy volunteers can be reasonably well predicted from preclinical data with the IB-derisk tool. The translatability of preclinical studies can be improved by applying a higher reporting standard in IBs including comparable PK measurements across all preclinical and clinical studies.

Coughing is a common symptom in pediatric lung disease and cough frequency has been shown to be correlated to disease activity in several conditions. Automated cough detection could provide a noninvasive digital biomarker for pediatric clinical trials or care. The aim of this study was to develop a smartphone‐based algorithm that objectively and automatically counts cough sounds of children.

Background Digital biomarkers are a promising novel method to capture clinical data in a home setting. However, clinical validation prior to implementation is of vital importance. The aim of this study was to clinically validate physical activity, heart rate, sleep and forced expiratory volume in 1 s (FEV1) as digital biomarkers measured by a smartwatch and portable spirometer in children with asthma and cystic fibrosis (CF). Methods This was a prospective cohort study including 60 children with asthma and 30 children with CF (aged 6–16 years). Participants wore a smartwatch, performed daily spirometry at home and completed a daily symptom questionnaire for 28 days. Physical activity, heart rate, sleep and FEV1 were considered candidate digital end-points. Data from 128 healthy children were used for comparison. Reported outcomes were compliance, difference between patients and controls, correlation with disease activity, and potential to detect clinical events. Analysis was performed with linear mixed effects models. Results Median compliance was 88%. On average, patients exhibited lower physical activity and FEV1 compared with healthy children, whereas the heart rate of children with asthma was higher compared with healthy children. Days with a higher symptom score were associated with lower physical activity for children with uncontrolled asthma and CF. Furthermore, FEV1 was lower and (nocturnal) heart rate was higher for both patient groups on days with more symptoms. Candidate biomarkers appeared able to describe a pulmonary exacerbation. Conclusions Portable spirometer- and smartwatch-derived digital biomarkers show promise as candidate end-points for use in clinical trials or clinical care in paediatric lung disease. Portable spirometer- and smartwatch-derived digital biomarkers of physical activity, heart rate and FEV1 show promise as candidate end-points for use in clinical trials or clinical care in paediatric asthma and cystic fibrosis https://bit.ly/3DIkzIt

Background: Intranasal esketamine demonstrates rapid improvement of depressive symptoms. However, transient adverse effects (dissociation, sedation and dizziness) may occur, which could impact driving performance. Aims: To evaluate the effects of 84 mg intranasal esketamine on driving performance in unipolar major depressive disorder (MDD) or persistent depressive disorder (PDD) patients. Methods: The study consisted of two parts. Part A was a single-blind, double-dummy, randomized three-period, cross-over study to compare effects of esketamine versus placebo on next morning driving, 18 ± 2 h post-treatment. Alcohol was administered to demonstrate assay sensitivity. In Part B, same-day driving, 6 ± 0.5 hours post-treatment, was assessed during twice weekly esketamine administration for 3 weeks. Twenty-seven patients with mild-to-moderate MDD or PDD without psychotic features completed a 100 km on-the-road driving test on a public highway in normal traffic. The primary outcome was standard deviation of lateral position (SDLP; cm; weaving of car). Results: In Part A, alcohol impaired driving performance compared to placebo: Least-square means (95% CI), p-value for delta SDLP (cm) compared with placebo: (ΔSDLP = + 1.83 (1.03; 2.62), p < 0.001), whereas esketamine did not: (ΔSDLP = −0.23 (−1.04; 0.58), p = 0.572). In Part B, weekly driving tests showed no differences between placebo baseline SDLP and after esketamine administration over 3 weeks: Day 11: (ΔSDLP = −0.96 (−3.72; 1.81), p = 0.493), Day 18: (ΔSDLP = −0.56 (−3.33; 2.20), p = 0.686) and Day 25: (ΔSDLP = −1.05 (−3.82; 1.71), p = 0.451). Conclusions: In this study, esketamine did not impair on-road driving performance the next morning following a single dose, or on same day after repeated administration.

Introduction: Clinical research and treatment of childhood obesity is challenging, and objective biomarkers obtained in a home-setting are needed. The aim of this study was to determine the potential of novel digital endpoints gathered by a home-monitoring platform in pediatric obesity. Methods: In this prospective observational study, 28 children with obesity aged 6–16 years were included and monitored for 28 days. Patients wore a smartwatch, which measured physical activity (PA), heart rate (HR), and sleep. Furthermore, daily blood pressure (BP) measurements were performed. Data from 128 healthy children were utilized for comparison. Differences between patients and controls were assessed via linear mixed effect models. Results: Data from 28 patients (average age 11.6 years, 46% male, average body mass index 30.9) and 128 controls (average age 11.1 years, 46% male, average body mass index 18.0) were analyzed. Patients were recruited between November 2018 and February 2020. For patients, the median compliance for the measurements ranged from 55% to 100% and the highest median compliance was observed for the smartwatch-related measurements (81–100%). Patients had a lower daily PA level (4,597 steps vs. 6,081 steps, 95% confidence interval [CI] 862–2,108) and peak PA level (1,115 steps vs. 1,392 steps, 95% CI 136–417), a higher nighttime HR (81 bpm vs. 71 bpm, 95% CI 6.3–12.3) and daytime HR (98 bpm vs. 88 bpm, 95% CI 7.6–12.6), a higher systolic BP (115 mm Hg vs. 104 mm Hg, 95% CI 8.1–14.5) and diastolic BP (76 mm Hg vs. 65 mm Hg, 95% CI 8.7–12.7), and a shorter sleep duration (difference 0.5 h, 95% CI 0.2–0.7) compared to controls. Conclusion: Remote monitoring via wearables in pediatric obesity has the potential to objectively measure the disease burden in the home-setting. The novel endpoints demonstrate significant differences in PA level, HR, BP, and sleep duration between patients and controls. Future studies are needed to determine the capacity of the novel digital endpoints to detect effect of interventions.

ModraPac001 (MP1) and ModraPac005 (MP5) are novel oral paclitaxel formulations that are coadministered with the cytochrome P450 3A4 inhibitor ritonavir (r), enabling daily low-dose metronomic (LDM) treatment. The primary aim of this study was to determine the safety, pharmacokinetics and maximum tolerated dose (MTD) of MP1/r and MP5/r. The second aim was to establish the recommended phase 2 dose (RP2D) as LDM treatment. This was an open-label phase 1 trial. Patients with advanced solid tumors were enrolled according to a classical 3+3 design. After initial employment of the MP1 capsule, the MP5 tablet was introduced. Safety was assessed using the Common Terminology Criteria for Adverse Events version 4.02. Pharmacokinetic sampling was performed on days 1, 2, 8, and 22 for determination of paclitaxel and ritonavir plasma concentrations. In this study, 37 patients were treated with up to twice-daily 30-mg paclitaxel combined with twice-daily 100-mg ritonavir (MP5/r 30-30/100-100) in 9 dose levels. Dose-limiting toxicities were nausea, (febrile) neutropenia, dehydration and vomiting. At the MTD/RP2D of MP5/r 20-20/100-100, the maximum paclitaxel plasma concentration and area under the concentration-time curve until 24 hours were 34.6 ng/mL (coefficient of variation, 79%) and 255 ng • h/mL (coefficient of variation, 62%), respectively. Stable disease was observed as best response in 15 of 31 evaluable patients. Based on these results, LDM therapy with oral paclitaxel coadministrated with ritonavir was considered feasible and safe. The MTD and RP2D were determined as MP5/r 20-20/100-100. Further clinical development of MP5/r as an LDM concept, including potential combination treatment, is warranted.

Background: Historically, pharmacokinetic (PK) studies and therapeutic drug monitoring (TDM) have relied on plasma as a sampling matrix. Noninvasive sampling matrices, such as saliva, can reduce the burden on pediatric patients. The variable plasma-saliva relationship can be quantified using population PK models (nonlinear mixed-effect models). However, criteria regarding acceptable levels of variability in such models remain unclear. In this simulation study, the authors aimed to propose a saliva TDM evaluation framework and evaluate model requirements in the context of TDM, with gentamicin and lamotrigine as model compounds. Methods: Two population pharmacokinetic models for gentamicin in neonates and lamotrigine in pediatrics were extended with a saliva compartment including a delay constant (k(SALIVA)), a saliva:plasma ratio, and between-subject variability (BSV) on both parameters. Subjects were simulated using a realistic covariate distribution. Bayesian maximum a posteriori TDM was applied to assess the performance of an increasing number of TDM saliva samples and varying levels of BSV and residual variability. Saliva TDM performance was compared with plasma TDM performance. The framework was applied to a known voriconazole saliva model as a case study. Results: TDM performed using saliva resulted in higher target attainment than no TDM, and a residual proportional error <25% on saliva observations led to saliva TDM performance comparable with plasma TDM. BSV on k(SALIVA) did not affect performance, whereas increasing BSV on saliva:plasma ratios by >25% for gentamicin and >50% for lamotrigine reduced performance. The simulated target attainment for voriconazole saliva TDM was >90%. Conclusions: Saliva as an alternative matrix for noninvasive TDM is possible using nonlinear mixed-effect models combined with Bayesian optimization. This article provides a workflow to explore TDM performance for compounds measured in saliva and can be used for evaluation during model building.

Abstract Dexamethasone has antitumor activity in metastatic castration resistant prostate cancer (mCRPC). We aimed to investigate intravenous liposome‐encapsulated dexamethasone disodium phosphate (liposomal dexamethasone) administration in mCRPC patients. In this exploratory first‐in‐man study, patients in part A received a starting dose of 10 mg followed by five doses of 20 mg liposomal dexamethasone at 2‐week intervals. Upon review of part A safety, patients in part B received 10 weekly doses of 18.5 mg. Primary outcomes were safety and pharmacokinetic profile, secondary outcome was antitumor efficacy. Nine mCRPC patients (5 part A, 4 part B) were enrolled. All patients experienced grade 1–2 toxicity, one (part B) patient experienced grade 3 toxicity (permanent bladder catheter‐related urosepsis). No infusion‐related adverse events occurred. One patient had upsloping glucose levels ≤9.1 mmol/L. Trough plasma concentrations of liposomal‐ and free dexamethasone were below the lower limit of quantification (LLOQ) in part A, and above LLOQ in three patients in part B (t1/2 ~50 h for liposomal dexamethasone), trough concentrations of liposomal‐ and free dexamethasone increased toward the end of the study. In seven of nine patients (78%) patients, stable disease was observed in bone and/or CT scans at follow‐up, and in one (part B) of these seven patients a >50% PSA biochemical response was observed. Bi‐ and once weekly administrations of IV liposomal dexamethasone were well‐tolerated. Weekly dosing enabled trough concentrations of liposomal‐ and free dexamethasone >LLOQ. The data presented support further clinical investigation in well‐powered studies. Clinical trial registration: ISRCTN 10011715.

Introduction: The duration and frequency of crying of an infant can be indicative of its health. Manual tracking and labeling of crying is laborious, subjective, and sometimes inaccurate. The aim of this study was to develop and technically validate a smartphone-based algorithm able to automatically detect crying. Methods: For the development of the algorithm a training dataset containing 897 5-s clips of crying infants and 1,263 clips of non-crying infants and common domestic sounds was assembled from various online sources. OpenSMILE software was used to extract 1,591 audio features per audio clip. A random forest classifying algorithm was fitted to identify crying from non-crying in each audio clip. For the validation of the algorithm, an independent dataset consisting of real-life recordings of 15 infants was used. A 29-min audio clip was analyzed repeatedly and under differing circumstances to determine the intra- and inter- device repeatability and robustness of the algorithm. Results: The algorithm obtained an accuracy of 94% in the training dataset and 99% in the validation dataset. The sensitivity in the validation dataset was 83%, with a specificity of 99% and a positive- and negative predictive value of 75 and 100%, respectively. Reliability of the algorithm appeared to be robust within- and across devices, and the performance was robust to distance from the sound source and barriers between the sound source and the microphone. Conclusion: The algorithm was accurate in detecting cry duration and was robust to various changes in ambient settings.

Background Digital devices and wearables allow for the measurement of a wide range of health-related parameters in a non-invasive manner, which may be particularly valuable in pediatrics. Incorporation of such parameters in clinical trials or care as digital endpoint could reduce the burden for children and their parents but requires clinical validation in the target population. This study aims to determine the tolerability, repeatability, and reference values of novel digital endpoints in healthy children. Methods Apparently healthy children (n = 175, 46% male) aged 2–16 were included. Subjects were monitored for 21 days using a home-monitoring platform with several devices (smartwatch, spirometer, thermometer, blood pressure monitor, scales). Endpoints were analyzed with a mixed effects model, assessing variables that explained within- and between-subject variability. Endpoints based on physical activity, heart rate, and sleep-related parameters were included in the analysis. For physical-activity-related endpoints, a sample size needed to detect a 15% increase was calculated. Findings Median compliance was 94%. Variability in each physical activity-related candidate endpoint was explained by age, sex, watch wear time, rain duration per day, average ambient temperature, and population density of the city of residence. Estimated sample sizes for candidate endpoints ranged from 33–110 per group. Daytime heart rate, nocturnal heart rate and sleep duration decreased as a function of age and were comparable to reference values published in the literature. Conclusions Wearable- and portable devices are tolerable for pediatric subjects. The raw data, models and reference values presented here can be used to guide further validation and, in the future, clinical trial designs involving the included measures.

Background: Pediatric patients admitted for acute lung disease are treated and monitored in the hospital, after which full recovery is achieved at home. Many studies report in-hospital recovery, but little is known regarding the time to full recovery after hospital discharge. Technological innovations have led to increased interest in home-monitoring and digital biomarkers. The aim of this study was to describe at-home recovery of 3 common pediatric respiratory diseases using a questionnaire and wearable device. Methods: In this study, patients admitted due to pneumonia (n = 30), preschool wheezing (n = 30), and asthma exacerbation (AE; n = 11) were included. Patients were monitored with a smartwatch and a questionnaire during admission, with a 14-day recovery period and a 10-day “healthy” period. Median compliance was calculated, and a mixed-effects model was fitted for physical activity and heart rate (HR) to describe the recovery period, and the physical activity recovery trajectory was correlated to respiratory symptom scores. Results: Median compliance was 47% (interquartile range [IQR] 33–81%) during the entire study period, 68% (IQR 54–91%) during the recovery period, and 28% (IQR 0–74%) during the healthy period. Patients with pneumonia reached normal physical activity 12 days postdischarge, while subjects with wheezing and AE reached this level after 5 and 6 days, respectively. Estimated mean physical activity was closely correlated with the estimated mean symptom score. HR measured by the smartwatch showed a similar recovery trajectory for subjects with wheezing and asthma, but not for subjects with pneumonia. Conclusions: The digital biomarkers, physical activity, and HR obtained via smartwatch show promise for quantifying postdischarge recovery in a noninvasive manner, which can be useful in pediatric clinical trials and clinical care.

Objective: Osteoarthritis (OA) is the most common cause of disability in older adults, and leads to a huge unmet medical need, as no registered disease modifying OA drugs (DMOADs), but only symptomatic treatments, are available. New targets and compounds for these targets, are currently under investigation. The objective of this paper is to provide an overview of compounds under investigation for OA in phase II and III. Design: We performed a review of OA trials for pharmacological interventions registered on the National Library of Medicine ClinicalTrials.gov website with a completion date in 2017 or later. Results: The database search yielded 255 results, of which 184 studies were included in this review. These were structured in compounds targeting pain, immunomodulators, stem cell therapy, platelet rich plasma and DMOADs with cartilage and/or bone resorption modifying properties. Conclusions: The results provide an overview of the fields in development and may include future treatment options for OA, by which a registered DMOADs may become more than a utopic vista. Further knowledge on pathophysiology and new approaches of value-based drug development could be an opportunity for the optimization of drug development in OA.

Diagnosis and follow‐up of respiratory diseases traditionally rely on pulmonary function tests (PFTs), which are currently performed in hospitals and require trained personnel. Smartphone‐connected spirometers, like the Air Next spirometer, have been developed to aid in the home monitoring of patients with pulmonary disease. The aim of this study was to investigate the technical validity and usability of the Air Next spirometer in pediatric patients.

AbstractOral administration of docetaxel in combination with the CYP3A4 inhibitor ritonavir is used in clinical trials to improve oral bioavailability of docetaxel. Diarrhea was the most commonly observed and dose‐limiting toxicity. This study combined preclinical and clinical data and investigated incidence, severity and cause of oral docetaxel‐induced diarrhea. In this study, incidence and severity of diarrhea in patients were compared to exposure to orally administered docetaxel. Intestinal toxicity after oral or intraperitoneal administration of docetaxel was further explored in mice lacking Cyp3a and mice lacking both Cyp3a and P‐glycoprotein. In patients, severity of diarrhea increased significantly with an increase in AUC and Cmax (P = .035 and P = .025, respectively), but not with an increase in the orally administered dose (P = .11). Furthermore, incidence of grade 3/4 diarrhea after oral docetaxel administration was similar as reported after intravenous docetaxel administration. Intestinal toxicity in mice was only observed at high systemic exposure to docetaxel and was similar after oral and intraperitoneal administration of docetaxel. In conclusion, our data show that the onset of severe diarrhea after oral administration of docetaxel in humans is similar after oral and intravenous administration of docetaxel and is caused by the concentration of docetaxel in the systemic blood circulation. Mouse experiments confirmed that intestinal toxicity is caused by a high systemic exposure and not by local intestinal exposure. Severe diarrhea in patients after oral docetaxel is reversible and is not related to the route of administration of docetaxel.

Novel digital endpoints gathered via wearables, small devices, or algorithms hold great promise for clinical trials. However, implementation has been slow because of a lack of guidelines regarding the validation process of these new measurements. In this paper, we propose a pragmatic approach toward selection and fit-for-purpose validation of digital endpoints. Measurements should be value-based, meaning the measurements should directly measure or be associated with meaningful outcomes for patients. Devices should be assessed regarding technological validity. Most importantly, a rigorous clinical validation process should appraise the tolerability, difference between patients and controls, repeatability, detection of clinical events, and correlation with traditional endpoints. When technically and clinically fit-for-purpose, case building in interventional clinical trials starts to generate evidence regarding the response to new or existing health-care interventions. This process may lead to the digital endpoint replacing traditional endpoints, such as clinical rating scales or questionnaires in clinical trials. We recommend initiating more data-sharing collaborations to prevent unnecessary duplication of research and integration of value-based measurements in clinical care to enhance acceptance by health-care professionals. Finally, we invite researchers and regulators to adopt this approach to ensure a timely implementation of digital measurements and value-based thinking in clinical trial design and health care. Significance Statement-Novel digital endpoints are often cited as promising for the clinical trial of the future. However, clear validation guidelines are lacking in the literature. This paper contains pragmatic criteria for the selection, technical validation, and clinical validation of novel digital endpoints and provides recommendations for future work and collaboration.

ModraPac001 (MP1) and ModraPac005 (MP5) are novel oral paclitaxel formulations that are coadministered with the cytochrome P450 3A4 inhibitor ritonavir (r), enabling daily low‐dose metronomic (LDM) treatment. The primary aim of this study was to determine the safety, pharmacokinetics and maximum tolerated dose (MTD) of MP1/r and MP5/r. The second aim was to establish the recommended phase 2 dose (RP2D) as LDM treatment. This was an open‐label phase 1 trial. Patients with advanced solid tumors were enrolled according to a classical 3+3 design. After initial employment of the MP1 capsule, the MP5 tablet was introduced. Safety was assessed using the Common Terminology Criteria for Adverse Events version 4.02. Pharmacokinetic sampling was performed on days 1, 2, 8, and 22 for determination of paclitaxel and ritonavir plasma concentrations. In this study, 37 patients were treated with up to twice‐daily 30‐mg paclitaxel combined with twice‐daily 100‐mg ritonavir (MP5/r 30‐30/100‐100) in 9 dose levels. Dose‐limiting toxicities were nausea, (febrile) neutropenia, dehydration and vomiting. At the MTD/RP2D of MP5/r 20‐20/100‐100, the maximum paclitaxel plasma concentration and area under the concentration‐time curve until 24 hours were 34.6 ng/mL (coefficient of variation, 79%) and 255 ng • h/mL (coefficient of variation, 62%), respectively. Stable disease was observed as best response in 15 of 31 evaluable patients. Based on these results, LDM therapy with oral paclitaxel coadministrated with ritonavir was considered feasible and safe. The MTD and RP2D were determined as MP5/r 20‐20/100‐100. Further clinical development of MP5/r as an LDM concept, including potential combination treatment, is warranted.

Purpose Recombinant human erythropoietin (rHuEPO) is known to increase thrombotic risk in patients and might have similar effects in athletes abusing the drug. rHuEPO is prohibited by anti-doping legislation, but this risk has not been investigated thoroughly. This analysis was designed to evaluate whether rHuEPO impacts hemostatic profile and endothelial and platelet activation markers in trained subjects, and whether the combination with exercise affects exercise induced alterations. Methods This double-blind, randomized, placebo-controlled trial enrolled healthy, trained male cyclists aged 18–50 years. Participants were randomly allocated (1:1) to receive subcutaneous injections of rHuEPO (epoetin-β; mean dose 6000 IU per week) or placebo (0.9% NaCl) for 8 weeks. Subjects performed five maximal exercise tests and a road race, coagulation and endothelial/platelet markers were measured at rest and directly after each exercise effort. Results rHuEPO increased P-selectin (+ 7.8% (1.5–14.5), p = 0.02) and E-selectin (+ 8.6% (2.0–15.7), p = 0.01) levels at rest. Maximal exercise tests significantly influenced all measured coagulation and endothelial/platelet markers, and in the rHuEPO group maximal exercise tests led to 15.3% ((7.0–24.3%), p = 0.0004) higher E-selectin and 32.1% ((4.6–66.8%), p = 0.0207) higher Platelet factor 4 (PF4) levels compared to the placebo group. Conclusion In conclusion, rHuEPO treatment resulted in elevated E- and P-selectin levels in trained cyclists, indicating enhanced endothelial activation and/or platelet reactivity. Exercise itself induces hypercoagulability, and the combination of rHuEPO and exercise increased E-selectin and PF4 levels more than either intervention alone. Based on this, exercise potentially increases thrombotic risk, a risk that might be enhanced in combination with rHuEPO use.