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Abstract C–C Motif Chemokine Ligand 17 (CCL17) is a chemokine that binds and signals through the G‐protein coupled CC‐chemokine receptor 4 and has been implicated in the development of inflammatory and arthritic pain. GSK3858279 is a high‐affinity, first‐in‐class, monoclonal antibody, binding specifically to CCL17 and inhibiting downstream signaling. In this phase I, randomized, single‐center, double‐blind, placebo‐controlled, three‐period, incomplete‐block crossover study (NCT04114656), the analgesic effects and safety of intravenous GSK3858279 were assessed in a battery of evoked acute pain assessments on healthy, adult (aged ≥18 years), male participants. Participants were randomized 1:1 to receive either one placebo (0.9% w/v NaCl) dose followed by two GSK3858279 doses (PAA treatment sequence), or one GSK3858279 dose followed by two placebo doses (APP treatment sequence). The co‐primary end points were ultraviolet B heat pain detection threshold (°C), cold pressor time to pain tolerance threshold (PTT, sec), and electrical PTT (mA, single stimulus). Twenty‐one participants were enrolled (PAA = 11; APP = 10). Mean age (standard deviation) was 29.3 (7.9) years for PAA, 31.1 (7.7) years for APP. No significant differences were observed in the analgesic effect between GSK3858279 and placebo for any end point. Exposure to GSK3858279 was similar between Period 1 (APP sequence), and Periods 2 and 3 (PAA sequence), with some GSK3858279 carry‐over. Changes in serum CCL17 levels were consistent with the expected GSK3858279 activity. All drug‐related adverse events were mild in intensity and caused no discontinuations. The absence of an efficacy signal in this acute pain model does not preclude efficacy in chronic pain states.

Abstract Dynamic balance assessments such as walking adaptability may yield a more realistic prediction of drug‐induced falls compared with postural stability measurements, as falls often result from limited gait adjustments when walking. The Interactive Walkway (IWW) measures walking adaptability but sensitivity to medication effects is unknown. If proven sensitive and specific, IWW could serve as a biomarker for targeted fall‐risk assessments in early clinical drug development. In this three‐way crossover study, 18 healthy elderly (age: 65–80 years) subjects received 5 mg zolpidem, 10 mg suvorexant, or placebo in the morning. Assessments were performed pre‐dose and approximately hourly until 9 h post‐dose. IWW assessments included an 8‐meter walking test, goal‐directed stepping, obstacle‐avoidance, and tandem‐walking. Other pharmacodynamic measurements were the Timed‐Up‐and‐Go (TUG) test at a comfortable and fast pace, adaptive tracking, and body sway. A decline in performance was observed for zolpidem compared with placebo for 3 h post‐dose in IWW walking adaptability outcome measures, TUG, adaptive tracking, and body sway. For the IWW tasks, a decrease in walking speed (among others) was observed. IWW parameters were not affected by suvorexant compared with placebo at any timepoint. However, an increase of 9.8% (95%CI: 1.8%, 18.5%) in body sway was observed for suvorexant compared with placebo up to 3 h post‐dose. The IWW successfully quantified drug effects of two hypnotic drugs and distinguished between zolpidem and suvorexant regarding their effects on walking. As a biomarker, the IWW demonstrated sensitivity in assessing dynamic balance and potential fall risk in early phase clinical drug development.

Abstract Apomorphine, used to treat OFF episodes in patients with Parkinson's disease (PD), is typically administered via subcutaneous injections. Administration of an oromucosal solution could offer a non‐invasive and user‐friendly alternative. This two‐part clinical study evaluated the safety, tolerability, pharmacokinetics (PK), and dose proportionality of a novel apomorphine hydrochloride oromucosal solution, as well as its relative bioavailability to subcutaneous apomorphine injection and apomorphine sublingual film. In part A of the study, 12 patients with PD received 2 mg oromucosal apomorphine (4% weight/volume) and 2 mg subcutaneous apomorphine in a randomized order, followed by 4 and 8 mg oromucosal apomorphine. In part B of the study, 13 patients with PD received 7 mg oromucosal apomorphine (7% weight/volume) and 30 mg sublingual apomorphine in a randomized order, followed by 14 mg oromucosal apomorphine. Washout between dose administrations in both study parts was at least 2 days. Safety, tolerability, and PK were assessed pre‐ and post‐dose. Both study parts showed that oromucosal apomorphine was generally well‐tolerated. Observed side effects were typical for apomorphine administration and included asymptomatic orthostatic hypotension, yawning, fatigue, and somnolence. Oromucosal apomorphine exposure increased with dose, although less than dose proportional. The mean (SD) maximum exposure reached with 14 mg oromucosal apomorphine was 753.0 (298.6) ng*min/mL (area under the plasma concentration–time curve from zero to infinity) and 8.0 (3.3) ng/mL (maximum plasma concentration). This was comparable to exposure reached after 2 mg subcutaneous apomorphine and approximately half of the exposure observed with 30 mg sublingual apomorphine. In summary, clinically relevant plasma concentrations could be reached in PD patients without tolerability issues.

Abstract Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of this study is to identify the correlations between remotely monitored self-reported assessments and objectively measured activities with depression severity assessments often applied in clinical trials. 30 unipolar depressed patients and 29 age- and gender-matched healthy controls were enrolled in this study. Each participant’s daily physiological, physical, and social activity were monitored using a smartphone-based application (CHDR MORE™) for 3 weeks continuously. Self-reported depression anxiety stress scale-21 (DASS-21) and positive and negative affect schedule (PANAS) were administered via smartphone weekly and daily respectively. The structured interview guide for the Hamilton depression scale and inventory of depressive symptomatology–clinical rated (SIGHD-IDSC) was administered in-clinic weekly. Nested cross-validated linear mixed-effects models were used to identify the correlation between the CHDR MORE™ features with the weekly in-clinic SIGHD-IDSC scores. The SIGHD-IDSC regression model demonstrated an explained variance (R2) of 0.80, and a Root Mean Square Error (RMSE) of ± 15 points. The SIGHD-IDSC total scores were positively correlated with the DASS and mean steps-per-minute, and negatively correlated with the travel duration. Unobtrusive, remotely monitored behavior and self-reported outcomes are correlated with depression severity. While these features cannot replace the SIGHD-IDSC for estimating depression severity, it can serve as a complementary approach for assessing depression and drug effects outside the clinic.

Abstract Increased leucine‐rich repeat kinase 2 (LRRK2) kinase activity is an established risk factor for Parkinson's disease (PD), and several LRRK2 kinase inhibitors are in clinical development as potential novel disease‐modifying therapeutics. This biomarker characterization study explored within‐ and between‐subject variability of multiple LRRK2 pathway biomarkers (total LRRK2 [tLRRK2], phosphorylation of the serine 935 (Ser935) residue on LRRK2 [pS935], phosphorylation of Rab10 [pRab10], and total Rab10 [tRab10]) in different biological sources (whole blood, peripheral blood mononuclear cells [PBMCs], neutrophils) as candidate human target engagement and pharmacodynamic biomarkers for implementation in phase I/II pharmacological studies of LRRK2 inhibitors. PD patients with a LRRK2 mutation (n = 6), idiopathic PD patients (n = 6), and healthy matched control subjects (n = 10) were recruited for repeated blood and cerebrospinal fluid (CSF) sampling split over 2 days. Within‐subject variability (geometric coefficient of variation [CV], %) of these biomarkers was lowest in whole blood and neutrophils (range: 12.64%–51.32%) and considerably higher in PBMCs (range: 34.81%–273.88%). Between‐subject variability displayed a similar pattern, with relatively lower variability in neutrophils (range: 61.30%–66.26%) and whole blood (range: 44.94%–123.11%), and considerably higher variability in PBMCs (range: 189.60%–415.19%). Group‐level differences were observed with elevated mean pRab10 levels in neutrophils and a reduced mean pS935/tLRRK2 ratio in PBMCs in PD LRRK2‐mutation carriers compared to healthy controls. These findings suggest that the evaluated biomarkers and assays could be used to verify pharmacological mechanisms of action and help explore the dose–response of LRRK2 inhibitors in early‐phase clinical studies. In addition, comparable α‐synuclein aggregation in CSF was observed in LRRK2‐mutation carriers compared to idiopathic PD patients.

Abstract Soluble guanylate cyclase (sGC) and its product, cyclic guanosine monophosphate, play a role in learning and memory formation. Zagociguat (CY6463) is a novel stimulator of sGC being developed for the treatment of neurodegenerative disease. Single zagociguat doses of 0.3, 1, 3, 10, 20, 30, and 50 mg were administered once to healthy participants in a single‐ascending‐dose phase; then zagociguat 2, 5, 10, and 15 mg was administered q.d. for 14 days in a multiple‐ascending‐dose phase; and, finally, zagociguat 10 mg was administered once in both fed and fasted state in a food‐interaction phase. Safety of zagociguat was evaluated by monitoring treatment‐emergent adverse events, suicide risk, vital signs, electrocardiography, and laboratory tests. Pharmacokinetics of zagociguat were assessed through blood, urine, and cerebrospinal fluid sampling. Pharmacodynamic effects of zagociguat were evaluated with central nervous system (CNS) tests and pharmaco‐electroencephalography. Zagociguat was well‐tolerated across all doses evaluated. Zagociguat exposures increased in a dose‐proportional manner. Median time to maximum concentration ranged from 0.8 to 5 h and mean terminal half‐life from 52.8 to 67.1 h. CNS penetration of the compound was confirmed by cerebrospinal fluid sampling. Zagociguat induced up to 6.1 mmHg reduction in mean systolic and up to 7.5 mmHg reduction in mean diastolic blood pressure. No consistent pharmacodynamic (PD) effects on neurocognitive function were observed. Zagociguat was well‐tolerated, CNS‐penetrant, and demonstrated PD activity consistent with other sGC stimulators. The results of this study support further development of zagociguat.

Abstract Low muscle quality and a sedentary lifestyle are indicators for a slow recovery after a total knee arthroplasty (TKA). Mitochondrial function is an important part of muscle quality and a key driver of sarcopenia. However, it is not known whether it relates to recovery. In this pilot study, we monitored activity after TKA using a wrist mounted activity tracker and assessed the relation of mitochondrial function on the rate of recovery after TKA. Additionally, we compared the increase in activity as a way to measure recovery to traditional outcome measures. Patients were studied 2 weeks before TKA and up to 6 months after. Activity was monitored continuously. Baseline mitochondrial function (citrate synthase and complex [CP] 1–5 abundance of the electron transport chain) was determined on muscle tissue taken during TKA. Traditional outcome measures (Knee Injury and Osteoarthritis Outcome Score [KOOS], timed up‐and‐go [TUG] completion time, grip, and quadriceps strength) were performed 2 weeks before, 6 weeks after, and 6 months after TKA. Using a multivariate regression model with various clinical baseline parameters, the following were significantly related to recovery: CP5 abundance, grip strength, and activity (regression weights 0.13, 0.02, and 2.89, respectively). During recovery, activity correlated to the KOOS‐activities of daily living (ADL) score (r = 0.55, p = 0.009) and TUG completion time (r = −0.61, p = 0.001). Mitochondrial function seems to be related to recovery, but so are activity and grip strength, all indicators of sarcopenia. Using activity trackers before and after TKA might give the surgeon valuable information on the expected recovery and the opportunity to intervene if recovery is low.

Abstract Measuring muscle velocity recovery cycles (MVRCs) is a method to obtain information on muscle cell excitability, independent of neuromuscular transmission. The goal was to validate MVRC as a pharmacodynamic (PD) biomarker for drugs targeting muscle excitability. As proof‐of‐concept, sensitivity of MVRC to detect effects of mexiletine, a voltage‐gated sodium channel (Nav) blocker, was assessed. In a randomized, double‐blind, two‐way crossover study, effects of a single pharmacologically active oral dose of 333 mg mexiletine was compared to placebo in 15 healthy male subjects. MVRC was performed predose, and 3‐ and 5‐h postdose using QTrac. Effects of mexiletine versus placebo were calculated using a mixed effects model with baseline as covariate. Mexiletine had significant effects on MVRC when compared to placebo. Early supernormality after five conditioning stimuli was decreased by mexiletine (estimated difference −2.78% [95% confidence interval: −4.16, −1.40]; p value = 0.0003). Moreover, mexiletine decreased the difference in late supernormality after five versus one conditioning stimuli (5XLSN; ED −1.46% [−2.26, −0.65]; p = 0.001). These results indicate that mexiletine decreases the percentage increase in velocity of the muscle fiber action potential after five conditioning stimuli, at long and short interstimulus intervals, which corresponds to a decrease in muscle membrane excitability. This is in line with the pharmacological activity of mexiletine, which leads to use‐dependent NaV1.4 blockade affecting muscle membrane potentials. This study shows that effects of mexiletine can be detected using MVRC in healthy subjects, thereby indicating that MVRC can be used as a tool to demonstrate PD effects of drugs targeting muscle excitability in early phase drug development.

Abstract Background This study investigated plasma biomarkers for neuroinflammation associated with Alzheimer’s disease (AD) in subjects with preclinical AD compared to healthy elderly. How these biomarkers behave in patients with AD, compared to healthy elderly is well known, but determining these in subjects with preclinical AD is not and will add information related to the onset of AD. When found to be different in preclinical AD, these inflammatory biomarkers may be used to select preclinical AD subjects who are most likely to develop AD, to participate in clinical trials with new disease-modifying drugs. Methods Healthy elderly (n= 50; age 71.9; MMSE >24) and subjects with preclinical AD (n=50; age 73.4; MMSE >24) defined by CSF Aβ1-42 levels < 1000 pg/mL were included. Four neuroinflammatory biomarkers were determined in plasma, GFAP, YKL-40, MCP-1, and eotaxin-1. Differences in biomarker outcomes were compared using ANCOVA. Subject characteristics age, gender, and APOE ε4 status were reported per group and were covariates in the ANCOVA. Least square means were calculated for all 4 inflammatory biomarkers using both the Aβ+/Aβ− cutoff and Ptau/Aβ1-42 ratio. Results The mean (standard deviation, SD) age of the subjects (n=100) was 72.6 (4.6) years old with 62 male and 38 female subjects. Mean (SD) overall MMSE score was 28.7 (0.49) and 32 subjects were APOE ε4 carriers. The number of subjects in the different APOE ε4 status categories differed significantly between the Aβ+ and Aβ− groups. Plasma GFAP concentration was significantly higher in the Aβ+ group compared to the Aβ− group with significant covariates age and sex, variables that also correlated significantly with GFAP. Conclusion GFAP was significantly higher in subjects with preclinical AD compared to healthy elderly which agrees with previous studies. When defining preclinical AD based on the Ptau181/Aβ1-42 ratio, YKL-40 was also significantly different between groups. This could indicate that GFAP and YKL-40 are more sensitive markers of the inflammatory process in response to the Aβ misfolding and aggregation that is ongoing as indicated by the lowered Aβ1-42 levels in the CSF. Characterizing subjects with preclinical AD using neuroinflammatory biomarkers is important for subject selection in new disease-modifying clinical trials. Trial registration ISRCTN.org identifier: ISRCTN79036545 (retrospectively registered).

Abstract RIPK1 is a master regulator of inflammatory signaling and cell death and increased RIPK1 activity is observed in human diseases, including Alzheimer’s disease (AD) and amyotrophic lateral sclerosis (ALS). RIPK1 inhibition has been shown to protect against cell death in a range of preclinical cellular and animal models of diseases. SAR443060 (previously DNL747) is a selective, orally bioavailable, central nervous system (CNS)–penetrant, small‐molecule, reversible inhibitor of RIPK1. In three early‐stage clinical trials in healthy subjects and patients with AD or ALS (NCT03757325 and NCT03757351), SAR443060 distributed into the cerebrospinal fluid (CSF) after oral administration and demonstrated robust peripheral target engagement as measured by a reduction in phosphorylation of RIPK1 at serine 166 (pRIPK1) in human peripheral blood mononuclear cells compared to baseline. RIPK1 inhibition was generally safe and well‐tolerated in healthy volunteers and patients with AD or ALS. Taken together, the distribution into the CSF after oral administration, the peripheral proof‐of‐mechanism, and the safety profile of RIPK1 inhibition to date, suggest that therapeutic modulation of RIPK1 in the CNS is possible, conferring potential therapeutic promise for AD and ALS, as well as other neurodegenerative conditions. However, SAR443060 development was discontinued due to long‐term nonclinical toxicology findings, although these nonclinical toxicology signals were not observed in the short duration dosing in any of the three early‐stage clinical trials. The dose‐limiting toxicities observed for SAR443060 preclinically have not been reported for other RIPK1‐inhibitors, suggesting that these toxicities are compound‐specific (related to SAR443060) rather than RIPK1 pathway‐specific.

BackgroundFacioscapulohumeral muscular dystrophy (FSHD) is a progressive neuromuscular disease. Its slow and variable progression makes the development of new treatments highly dependent on validated biomarkers that can quantify disease progression and response to drug interventions. ObjectiveWe aimed to build a tool that estimates FSHD clinical severity based on behavioral features captured using smartphone and remote sensor data. The adoption of remote monitoring tools, such as smartphones and wearables, would provide a novel opportunity for continuous, passive, and objective monitoring of FSHD symptom severity outside the clinic. MethodsIn total, 38 genetically confirmed patients with FSHD were enrolled. The FSHD Clinical Score and the Timed Up and Go (TUG) test were used to assess FSHD symptom severity at days 0 and 42. Remote sensor data were collected using an Android smartphone, Withings Steel HR+, Body+, and BPM Connect+ for 6 continuous weeks. We created 2 single-task regression models that estimated the FSHD Clinical Score and TUG separately. Further, we built 1 multitask regression model that estimated the 2 clinical assessments simultaneously. Further, we assessed how an increasingly incremental time window affected the model performance. To do so, we trained the models on an incrementally increasing time window (from day 1 until day 14) and evaluated the predictions of the clinical severity on the remaining 4 weeks of data. ResultsThe single-task regression models achieved an R2 of 0.57 and 0.59 and a root-mean-square error (RMSE) of 2.09 and 1.66 when estimating FSHD Clinical Score and TUG, respectively. Time spent at a health-related location (such as a gym or hospital) and call duration were features that were predictive of both clinical assessments. The multitask model achieved an R2 of 0.66 and 0.81 and an RMSE of 1.97 and 1.61 for the FSHD Clinical Score and TUG, respectively, and therefore outperformed the single-task models in estimating clinical severity. The 3 most important features selected by the multitask model were light sleep duration, total steps per day, and mean steps per minute. Using an increasing time window (starting from day 1 to day 14) for the FSHD Clinical Score, TUG, and multitask estimation yielded an average R2 of 0.65, 0.79, and 0.76 and an average RMSE of 3.37, 2.05, and 4.37, respectively. ConclusionsWe demonstrated that smartphone and remote sensor data could be used to estimate FSHD clinical severity and therefore complement the assessment of FSHD outside the clinic. In addition, our results illustrated that training the models on the first week of data allows for consistent and stable prediction of FSHD symptom severity. Longitudinal follow-up studies should be conducted to further validate the reliability and validity of the multitask model as a tool to monitor disease progression over a longer period. Trial RegistrationClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735

Abstract Selective inhibition of certain voltage‐gated sodium channels (Navs), such as Nav1.8, is of primary interest for pharmacological pain research and widely studied as a pharmacological target due to its contribution to repetitive firing, neuronal excitability, and pain chronification. VX‐128 is a highly potent and selective Nav1.8 inhibitor that was being developed as a treatment for pain. We evaluated the safety, tolerability, and pharmacokinetics of VX‐128 in healthy subjects in a single‐ and multiple‐ascending dose (MAD) first‐in‐human study. Pharmacodynamics were evaluated in the MAD part using a battery of evoked pain tests. Overall, single doses of VX‐128 up to 300 mg were well‐tolerated, although adverse effect (AE) incidence was higher in subjects receiving VX‐128 (41.7%) compared with placebo (25.0%). After multiple dosing of up to 10 days, skin rash events were observed at all dose levels (up to 100 mg once daily [q.d.]), in five of 26 (19.2%) subjects, including one subject receiving VX‐128 (100 mg q.d.) who had a serious AE of angioedema. A trend in pain tolerance were observed for cold pressor‐ and pressure pain, which was dose‐dependent for the latter. VX‐128 was rapidly absorbed (median time to maximum plasma concentration between 1 and 2 h) with a half‐life of ~80 h at 10 mg q.d., and approximately two‐fold accumulation ratio after 10 and 30 mg q.d. Although VX‐128, when given in a multiple dose fashion, resulted in early study termination due to tolerability issues, effects were observed on multiple pain tests that may support further investigation of Nav1.8 inhibitors as pain treatments.

Abstract The majority of disease modifying therapies for multiple sclerosis (MS) reduce inflammation, but do no’t target remyelination. Development of remyelinating therapies will benefit from a method to quantify myelin kinetics in patients with MS. We labeled myelin in vivo with deuterium, and modeled kinetics of myelin breakdown products β‐galactosylceramide (β‐GalC) and N‐Octadecanoyl‐sulfatide (NO‐Sulf). Five patients with MS received 120 ml 70% D2O daily for 70 days and were compared with six healthy subjects who previously received the same procedure. Mass spectrometry and compartmental modeling were used to quantify the turnover rate of β‐GalC and NO‐Sulf in cerebrospinal fluid (CSF). Turnover rate constants of the fractions of β‐GalC and NO‐Sulf with non‐negligible turnover were 0.00186 and 0.00714, respectively, in both healthy subjects and patients with MS. The turnover half‐life of β‐GalC and NO‐Sulf was calculated as 373 days and 96.5 days, respectively. The effect of MS on the NO‐Sulf (49.4% lower fraction with non‐negligible turnover) was more pronounced compared to the effect on β‐GalC turnover (18.3% lower fraction with non‐negligible turnover). Kinetics of myelin breakdown products in the CSF are different in patients with MS compared with healthy subjects. This may be caused by slower myelin production in these patients, by a higher level of degradation of a more stable component of myelin, or, most likely, by a combination of these two processes. Labeling myelin breakdown products is a useful method that can be used to quantify myelin turnover in patients with progressive MS and can therefore be used in proof‐of‐concept studies with remyelination therapies.

BackgroundFacioscapulohumeral dystrophy (FSHD) is a progressive muscle dystrophy disorder leading to significant disability. Currently, FSHD symptom severity is assessed by clinical assessments such as the FSHD clinical score and the Timed Up-and-Go test. These assessments are limited in their ability to capture changes continuously and the full impact of the disease on patients’ quality of life. Real-world data related to physical activity, sleep, and social behavior could potentially provide additional insight into the impact of the disease and might be useful in assessing treatment effects on aspects that are important contributors to the functioning and well-being of patients with FSHD. ObjectiveThis study investigated the feasibility of using smartphones and wearables to capture symptoms related to FSHD based on a continuous collection of multiple features, such as the number of steps, sleep, and app use. We also identified features that can be used to differentiate between patients with FSHD and non-FSHD controls. MethodsIn this exploratory noninterventional study, 58 participants (n=38, 66%, patients with FSHD and n=20, 34%, non-FSHD controls) were monitored using a smartphone monitoring app for 6 weeks. On the first and last day of the study period, clinicians assessed the participants’ FSHD clinical score and Timed Up-and-Go test time. Participants installed the app on their Android smartphones, were given a smartwatch, and were instructed to measure their weight and blood pressure on a weekly basis using a scale and blood pressure monitor. The user experience and perceived burden of the app on participants’ smartphones were assessed at 6 weeks using a questionnaire. With the data collected, we sought to identify the behavioral features that were most salient in distinguishing the 2 groups (patients with FSHD and non-FSHD controls) and the optimal time window to perform the classification. ResultsOverall, the participants stated that the app was well tolerated, but 67% (39/58) noticed a difference in battery life using all 6 weeks of data, we classified patients with FSHD and non-FSHD controls with 93% accuracy, 100% sensitivity, and 80% specificity. We found that the optimal time window for the classification is the first day of data collection and the first week of data collection, which yielded an accuracy, sensitivity, and specificity of 95.8%, 100%, and 94.4%, respectively. Features relating to smartphone acceleration, app use, location, physical activity, sleep, and call behavior were the most salient features for the classification. ConclusionsRemotely monitored data collection allowed for the collection of daily activity data in patients with FSHD and non-FSHD controls for 6 weeks. We demonstrated the initial ability to detect differences in features in patients with FSHD and non-FSHD controls using smartphones and wearables, mainly based on data related to physical and social activity. Trial RegistrationClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735

Abstract Background In the current study, we aimed to develop an algorithm based on biomarkers obtained through non- or minimally invasive procedures to identify healthy elderly subjects who have an increased risk of abnormal cerebrospinal fluid (CSF) amyloid beta42 (Aβ) levels consistent with the presence of Alzheimer’s disease (AD) pathology. The use of the algorithm may help to identify subjects with preclinical AD who are eligible for potential participation in trials with disease modifying compounds being developed for AD. Due to this pre-selection, fewer lumbar punctures will be needed, decreasing overall burden for study subjects and costs. Methods Healthy elderly subjects (n = 200; age 65–70 (N = 100) and age > 70 (N = 100)) with an MMSE > 24 were recruited. An automated central nervous system test battery was used for cognitive profiling. CSF Aβ1-42 concentrations, plasma Aβ1-40, Aβ1-42, neurofilament light, and total Tau concentrations were measured. Aβ1-42/1-40 ratio was calculated for plasma. The neuroinflammation biomarker YKL-40 and APOE ε4 status were determined in plasma. Different mathematical models were evaluated on their sensitivity, specificity, and positive predictive value. A logistic regression algorithm described the data best. Data were analyzed using a 5-fold cross validation logistic regression classifier. Results Two hundred healthy elderly subjects were enrolled in this study. Data of 154 subjects were used for the per protocol analysis. The average age of the 154 subjects was 72.1 (65–86) years. Twenty-four (27.3%) were Aβ positive for AD (age 65–83). The results of the logistic regression classifier showed that predictive features for Aβ positivity/negativity in CSF consist of sex, 7 CNS tests, and 1 plasma-based assay. The model achieved a sensitivity of 70.82% (± 4.35) and a specificity of 89.25% (± 4.35) with respect to identifying abnormal CSF in healthy elderly subjects. The receiver operating characteristic curve showed an AUC of 65% (± 0.10). Conclusion This algorithm would allow for a 70% reduction of lumbar punctures needed to identify subjects with abnormal CSF Aβ levels consistent with AD. The use of this algorithm can be expected to lower overall subject burden and costs of identifying subjects with preclinical AD and therefore of total study costs. Trial registration ISRCTN.org identifier: ISRCTN79036545 (retrospectively registered).

Abstract Altered motor neuron excitability in patients with amyotrophic lateral sclerosis (ALS) has been suggested to be an early pathophysiological mechanism associated with motor neuron death. Compounds that affect membrane excitability may therefore have disease‐modifying effects. Through which mechanism(s), these compounds modulate membrane excitability is mostly provided by preclinical studies, yet remains challenging to verify in clinical studies. Here, we investigated how retigabine affects human myelinated motor axons by applying computational modeling to interpret the complex excitability changes in a recent trial involving 18 ALS patients. Compared to baseline, the post‐dose excitability differences were modeled well by a hyperpolarizing shift of the half‐activation potential of slow potassium (K+)‐channels (till 2 mV). These findings verify that retigabine targets slow K+‐channel gating and highlight the usefulness of computational models. Further developments of this approach may facilitate the identification of early target engagement and ultimately aid selecting responders leading to more personalized treatment strategies.

AimTraditionally, early phase clinical trials in oncology have been performed in patients based on safety risk-benefit assessment. Therapeutic transition to immuno-oncology may open new opportunities for studies in healthy volunteers, which are conducted faster and are less susceptible to confounders. Aim of this study was to investigate to what extent this approach is utilized and whether pharmacodynamic endpoints are evaluated in these early phase trials. We conducted a comprehensive review of clinical trials with healthy volunteers using immunotherapies potentially relevant for oncology.MethodsLiterature searches according to PRISMA guidelines and after registration in PROSPERO were conducted in PubMed, Embase, Web of Science and Cochrane databases with the cut-off date 20 October 2020, using search terms of relevant targets in immuno-oncology. Articles describing clinical trials with immunotherapeutics in healthy volunteers with a mechanism relevant for oncology were included. “Immunotherapeutic” was defined as compounds exhibiting effects through immunological targets. Data including study design and endpoints were extracted, with specific attention to pharmacodynamic endpoints and safety.ResultsIn total, we found 38 relevant immunotherapeutic compounds tested in HVs, with 86% of studies investigating safety, 82% investigating the pharmacokinetics (PK) and 57% including at least one pharmacodynamic (PD) endpoint. Most of the observed adverse events (AEs) were Grade 1 and 2, consisting mostly of gastrointestinal, cutaneous and flu-like symptoms. Severe AEs were leukopenia, asthenia, syncope, headache, flu-like reaction and liver enzymes increase. PD endpoints investigated comprised of cytokines, immune and inflammatory biomarkers, cell counts, phenotyping circulating immune cells and ex vivo challenge assays.DiscussionHealthy volunteer studies with immuno-oncology compounds have been performed, although not to a large extent. The integration of healthy volunteers in well-designed proof-of-mechanism oriented drug development programs has advantages and could be pursued more in the future, since integrative clinical trial protocols may facilitate early dose selection and prevent cancer patients to be exposed to non-therapeutic dosing regimens.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=210861, identifier CRD42020210861

Abstract Background The cholinergic system and M1 receptor remain an important target for symptomatic treatment of cognitive dysfunction. The selective M1 receptor partial agonist HTL0018318 is under development for the symptomatic treatment of Dementia’s including Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB). We investigated the safety, tolerability, pharmacokinetics and exploratory pharmacodynamics of multiple doses of HTL0018318 in healthy younger adults and elderly subjects. Methods This randomised, double blind, placebo-controlled study was performed, investigating oral doses of 15–35 mg/day HTL0018318 or placebo in 7 cohorts of healthy younger adult (n = 36; 3 cohorts) and elderly (n = 50; 4 cohorts) subjects. Safety, tolerability and pharmacokinetic measurements were performed. Pharmacodynamics were assessed using a battery of neurocognitive tasks and electrophysiological biomarkers of synaptic and cognitive functions. Results HTL0018318 was generally well-tolerated in multiple doses up to 35 mg/day and were associated with mild or moderate cholinergic adverse events. There were modest increases in blood pressure and pulse rate when compared to placebo-treated subjects, with tendency for the blood pressure increase to attenuate with repeated dosing. There were no clinically significant observations or changes in blood and urine laboratory measures of safety or abnormalities in the ECGs and 24-h Holter assessments. HTL0018318 plasma exposure was dose-proportional over the range 15–35 mg. Maximum plasma concentrations were achieved after 1–2 h. The apparent terminal half-life of HTL0018318 was 16.1 h (± 4.61) in younger adult subjects and 14.3 h (± 2.78) in elderly subjects at steady state. HTL0018318 over the 10 days of treatment had significant effects on tests of short-term (working) memory (n-back) and learning (Milner maze) with moderate to large effect sizes. Conclusion Multiple doses of HTL0018138 showed well-characterised pharmacokinetics and were safe and generally well-tolerated in the dose range studied. Pro-cognitive effects on short-term memory and learning were demonstrated across the dose range. These data provide encouraging data in support of the development of HTL0018138 for cognitive dysfunction in AD and DLB. Trial registration Netherlands Trial Register identifier NTR5781 . Registered on 22 March 2016.

Background: Central nervous system (CNS) disorders benefit from ongoing monitoring to assess disease progression and treatment efficacy. Mobile health (mHealth) technologies offer a means for the remote and continuous symptom monitoring of patients. Machine Learning (ML) techniques can process and engineer mHealth data into a precise and multidimensional biomarker of disease activity. Objective: This narrative literature review aims to provide an overview of the current landscape of biomarker development using mHealth technologies and ML. Additionally, it proposes recommendations to ensure the accuracy, reliability, and interpretability of these biomarkers. Methods: This review extracted relevant publications from databases such as PubMed, IEEE, and CTTI. The ML methods employed across the selected publications were then extracted, aggregated, and reviewed. Results: This review synthesized and presented the diverse approaches of 66 publications that address creating mHealth-based biomarkers using ML. The reviewed publications provide a foundation for effective biomarker development and offer recommendations for creating representative, reproducible, and interpretable biomarkers for future clinical trials. Conclusion: mHealth-based and ML-derived biomarkers have great potential for the remote monitoring of CNS disorders. However, further research and standardization of study designs are needed to advance this field. With continued innovation, mHealth-based biomarkers hold promise for improving the monitoring of CNS disorders.

Abstract A variant in the GBA1 gene is one of the most common genetic risk factors to develop Parkinson’s disease (PD). Here the serendipitous finding is reported of a polymerase dependent allelic imbalance when using next generation sequencing, potentially resulting in false-negative results when the allele frequency falls below the variant calling threshold (by default commonly at 30%). The full GBA1 gene was sequenced using next generation sequencing on saliva derived DNA from PD patients. Four polymerase chain reaction conditions were varied in twelve samples, to investigate the effect on allelic imbalance: (1) the primers (n = 4); (2) the polymerase enzymes (n = 2); (3) the primer annealing temperature (Ta) specified for the used polymerase; and (4) the amount of DNA input. Initially, 1295 samples were sequenced using Q5 High-Fidelity DNA Polymerase. 112 samples (8.6%) had an exonic variant and an additional 104 samples (8.0%) had an exonic variant that did not pass the variant frequency calling threshold of 30%. After changing the polymerase to TaKaRa LA Taq DNA Polymerase Hot-Start Version: RR042B, all samples had an allele frequency passing the calling threshold. Allele frequency was unaffected by a change in primer, annealing temperature or amount of DNA input. Sequencing of the GBA1 gene using next generation sequencing might be susceptible to a polymerase specific allelic imbalance, which can result in a large amount of flase-negative results. This was resolved in our case by changing the polymerase. Regions displaying low variant calling frequencies in GBA1 sequencing output in previous and future studies might warrant additional scrutiny.

Sodium channel blockers are used for the treatment of pain, but this is limited by the lack of selectivity for different sodium channel subtypes, which can result in central nervous system and cardiovascular side effects. As such, there is special interest in the Nav1.7 subtype, which is expressed predominantly in nociceptive and sympathetic neurons. The aim was to demonstrate analgesic properties of a potent selective Nav1.7 sodium channel blocker, PF‐05089771, alone and concomitantly with pregabalin in healthy subjects using a battery of human evoked pain models. This was a double‐blind, double‐dummy, randomized, placebo‐controlled, five‐period cross‐over study with PF‐05089771 alone and PF‐05089771 concomitantly with pregabalin as treatment arms with pregabalin, ibuprofen, and placebo as control arms (NCT02349607). A battery of human evoked pain models was used to investigate analgesic properties of PF‐05089771. Twenty‐five subjects were enrolled in the study of which 23 subjects completed all five periods. PF‐05089771 alone did not differ from placebo on the primary pain end points. The same holds when comparing PF‐05089771 concomitantly with pregabalin and pregabalin alone. Pregabalin showed significant effects relative to placebo on thermal pain on the normal skin and UVB skin (least squares means with 90% confidence interval: 0.63 (0.32–0.93) and 0.53 (0.11–0.96)), pressure stimulation (1.10 (1.04–1.18)), and cold pressor (1.22 (1.14–1.32)). Ibuprofen demonstrated significant effects on thermal pain UVB skin (1.26 (0.82–1.70)) and pressure stimulation assessment (1.08 (1.01–1.15)), consistent with historical results. This study did not demonstrate analgesic properties of PF‐05089771 alone or concomitantly with pregabalin in a battery of pain models.

Abstract Background To date, no symptomatic treatment is available for patients with vascular cognitive impairment (VCI). In the proof-of-principle study Symptomatic Treatment of Vascular Cognitive Impairment (STREAM-VCI), we investigated whether a single dose of a monoaminergic drug (methylphenidate) improves executive functioning and whether a single dose of a cholinergic drug (galantamine) improves memory in VCI patients. Methods STREAM-VCI is a single-center, double-blind, three-way crossover trial. We included 30 VCI patients (Mini-Mental State Examination (MMSE) ≥ 16 and Clinical Dementia Rating score 0.5–1.0) with cerebrovascular pathology on MRI. All patients received single doses of methylphenidate (10 mg), galantamine (16 mg), and placebo in random order on three separate study visits. We used the NeuroCart®, a computerized test battery, to assess drug-sensitive cognitive effects. Predefined main outcomes, measured directly after a single dose of a study drug, were (i) change in performance on the adaptive tracker for executive functioning and (ii) performance on the Visual Verbal Learning Test-15 (VVLT-15) for memory, compared to placebo. We performed mixed model analysis of variance. Results The study population had a mean age of 67 ± 8 years and MMSE 26 ± 3, and 9 (30%) were female. Methylphenidate improved performance on the adaptive tracker more than placebo (mean difference 1.40%; 95% confidence interval [CI] 0.56–2.25; p = 0.002). In addition, methylphenidate led to better memory performance on the VVLT-15 compared to placebo (mean difference in recalled words 0.59; 95% CI 0.03–1.15; p = 0.04). Galantamine did not improve performance on the adaptive tracker and led to worse performance on delayed recall of the VVLT-15 (mean difference − 0.84; 95% CI − 1.65, − 0.03; p = 0.04). Methylphenidate was well tolerated while galantamine produced gastrointestinal side effects in a considerable number of patients. Conclusions In this proof-of-principle study, methylphenidate is well tolerated and improves executive functioning and immediate recall in patients with VCI. Galantamine did not improve memory or executive dysfunction. Results might be influenced by the considerable amount of side effects seen. Trial registration http://www.clinicaltrials.gov. Registration number: NCT02098824. Registration date: March 28, 2014.

BackgroundOpioid-induced respiratory depression driven by ligand binding to mu-opioid receptors is a leading cause of opioid-related fatalities. Buprenorphine, a partial agonist, binds with high affinity to mu-opioid receptors but displays partial respiratory depression effects. The authors examined whether sustained buprenorphine plasma concentrations similar to those achieved with some extended-release injections used to treat opioid use disorder could reduce the frequency and magnitude of fentanyl-induced respiratory depression.MethodsIn this two-period crossover, single-centre study, 14 healthy volunteers (single-blind, randomized) and eight opioid-tolerant patients taking daily opioid doses ≥90 mg oral morphine equivalents (open-label) received continuous intravenous buprenorphine or placebo for 360 minutes, targeting buprenorphine plasma concentrations of 0.2 or 0.5 ng/mL in healthy volunteers and 1.0, 2.0 or 5.0 ng/mL in opioid-tolerant patients. Upon reaching target concentrations, participants received up to four escalating intravenous doses of fentanyl. The primary endpoint was change in isohypercapnic minute ventilation (VE). Additionally, occurrence of apnea was recorded.ResultsFentanyl-induced changes in VE were smaller at higher buprenorphine plasma concentrations. In healthy volunteers, at target buprenorphine concentration of 0.5 ng/mL, the first and second fentanyl boluses reduced VE by [LSmean (95% CI)] 26% (13-40%) and 47% (37-59%) compared to 51% (38-64%) and 79% (69-89%) during placebo infusion (p = 0.001 and < .001, respectively). Discontinuations for apnea limited treatment comparisons beyond the second fentanyl injection. In opioid-tolerant patients, fentanyl reduced VE up to 49% (21-76%) during buprenorphine infusion (all concentration groups combined) versus up to 100% (68-132%) during placebo infusion (p = 0.006). In opioid-tolerant patients, the risk of experiencing apnea requiring verbal stimulation following fentanyl boluses was lower with buprenorphine than with placebo (odds ratio: 0.07; 95% CI: 0.0 to 0.3; p = 0.001).InterpretationResults from this proof-of-principle study provide the first clinical evidence that high sustained plasma concentrations of buprenorphine may protect against respiratory depression induced by potent opioids like fentanyl.

Background: Patients with vascular cognitive impairment (VCI) are very heterogeneous in both symptoms and type of cerebrovascular pathology. This might be an important reason why there is no symptomatic treatment available for VCI patients. In this study, we investigated in patients with VCI, whether there was an association between a positive response to methylphenidate and galantamine and the type of cerebrovascular disease, structural damage to specific neurotransmitter systems, cerebral perfusion, and presence of co-morbid Alzheimer (AD) pathology. Methods: We included 27 VCI patients (mean age 67 years ± 8,30% female) from the STREAM-VCI trial who received placebo, methylphenidate(10 mg), and galantamine(16 mg) in a single challenge, cross-over design. In this study, we classified patients improving on a task for executive functioning after methylphenidate compared to placebo as methylphenidate responders (MPH+; resp. non-responders, MPH−) and patients improving on a task for memory after galantamine compared to placebo as galantamine responders (GAL+; resp. non-responders, GAL−). On baseline MRI, we visually assessed measures of cerebrovascular disease, automatically segmented white matter hyperintensities, used diffusion tensor imaging to visualize the integrity of monoaminergic and cholinergic neurotransmitter systems with mean diffusivity (MD) and fractional anisotropy (FA). Comorbid AD pathology was assessed using CSF or amyloid-PET. We tested differences between responders and non-responders using ANOVA, adjusting for age and sex. Results: Nine patients were MPH+ vs 18 MPH−. MPH+ had higher MD (1.22 ± 0.07 vs 0.94 ± 0.05); p = .001) and lower FA (0.38 ± .01 vs 0.43 ± .01); p = .04) in the monoaminergic tract compared to MPH−. Eight patients were GAL+ and 18 GAL−. We found no differences between GAL+ and GAL− in any of the MRI measures. Information on co-morbid AD pathology was present in 17 patients. AD pathology tended to be more frequent in GAL+ vs GAL− (5(71%) vs 2(20%); p = .06). Conclusions: In patients with VCI, we found that decreased integrity of the monoaminergic tract is associated with a positive response to MPH. Responsiveness to galantamine may be related to co-morbid AD pathology.

Effective treatment for many pain disorders is still lacking, which is due to the complexity of pain in general and of the underlying pathology of many pain syndromes in particular. This results in the majority of investigational analgesic drugs failing to reach registration, either due to lack of efficacy, or due to the drug's adverse effect profile. To increase the number of analgesics that reach the patient, it is essential to carefully and rationally plan the clinical development program. By including proof-of-mechanism (PoM) and/or proof-of-concept (PoC) methods in early-phase clinical drug studies, the analgesic drug developer will be better informed regarding the key characteristics of the studied drug, which will aid in making crucial decisions during the development process. Here, we describe the top 10 currently most developed analgesic drug classes, link them mechanistically to appropriate methods to demonstrate PoM and PoC in early-phase clinical trials, and include pros and cons of each of the methods described. Lastly, we discuss how each analgesic drug class requires a tailored experimental approach for proper evaluation of PoM and PoC, and how this can contribute to an efficient and question-based approach in early-phase analgesic drug research.

Abstract Introduction Gln‐1062 (MEMOGAIN) is an intranasally administered lipophilic prodrug of galantamine. Based on high brain‐to‐blood concentrations observed in pre‐clinical studies, Gln‐1062 is expected to have superior cognitive efficacy compared to oral galantamine. Methods Forty‐eight healthy elderly subjects were randomized 12:4 to Gln‐1062 (5.5, 11, or 22 mg, b.i.d., for 7 days) or placebo. Safety, tolerability, pharmacokinetics, and pharmacodynamics were assessed repeatedly. Pharmacokinetics were compared with 16 mg oral galantamine. Results Gln‐1062 up to 22 mg, b.i.d., was well tolerated. Gln‐1062 plasma concentrations increased immediately following dosing (median Tmax of 0.5 hour [range 0.5‐1.0]). Cmax and AUC0‐last increased in a dose‐linear manner over all three dose levels. Gln‐1062 was rapidly cleaved into galantamine. Gln‐1062 significantly improved adaptive tracking (sustained attention) with 1.95% (95% confidence interval [CI] 0.630‐3.279, P = 0.0055) compared to placebo after correction for individual baseline performance. Discussion Gln‐1062 was considered to be safe and caused fewer gastrointestinal side effects than oral galantamine. Gln‐1062 behaved pharmacokinetically as expected and improved performance on cognitive tests.

Abstract Monitoring effects of disease or therapeutic intervention on brain function is increasingly important for clinical trials, albeit hampered by inter-individual variability and subtle effects. Here, we apply complementary biomarker algorithms to electroencephalography (EEG) recordings to capture the brain’s multi-faceted signature of disease or pharmacological intervention and use machine learning to improve classification performance. Using data from healthy subjects receiving scopolamine we developed an index of the muscarinic acetylcholine receptor antagonist (mAChR) consisting of 14 EEG biomarkers. This mAChR index yielded higher classification performance than any single EEG biomarker with cross-validated accuracy, sensitivity, specificity and precision ranging from 88–92%. The mAChR index also discriminated healthy elderly from patients with Alzheimer’s disease (AD); however, an index optimized for AD pathophysiology provided a better classification. We conclude that integrating multiple EEG biomarkers can enhance the accuracy of identifying disease or drug interventions, which is essential for clinical trials.

The clinical failure rate for disease-modifying treatments (DMTs) that slow or stop disease progression has been nearly 100% for the major neurodegenerative disorders (NDDs), with many compounds failing in expensive and time-consuming phase 2 and 3 trials for lack of efficacy. Here, we critically review the use of pharmacological and mechanistic biomarkers in early phase clinical trials of DMTs in NDDs, and propose a roadmap for providing early proof-of-concept to increase R&D productivity in this field of high unmet medical need. A literature search was performed on published early phase clinical trials aimed at the evaluation of NDD DMT compounds using MESH terms in PubMed. Publications were selected that reported an early phase clinical trial with NDD DMT compounds between 2010 and November 2020. Attention was given to the reported use of pharmacodynamic (mechanistic and physiological response) biomarkers. A total of 121 early phase clinical trials were identified, of which 89 trials (74%) incorporated one or multiple pharmacodynamic biomarkers. However, only 65 trials (54%) used mechanistic (target occupancy or activation) biomarkers to demonstrate target engagement in humans. The most important categories of early phase mechanistic and response biomarkers are discussed and a roadmap for incorporation of a robust biomarker strategy for early phase NDD DMT clinical trials is proposed. As our understanding of NDDs is improving, there is a rise in potentially disease-modifying treatments being brought to the clinic. Further increasing the rational use of mechanistic biomarkers in early phase trials for these (targeted) therapies can increase R&D productivity with a quick win/fast fail approach in an area that has seen a nearly 100% failure rate to date.

To diagnose and treat early-stage (preclinical) Alzheimer’s disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.