Pharmacokinetics and safety of candidate tocilizumab biosimilar CT-P47 administered by auto-injector or pre-filled syringe: a randomized, open­label, single-dose phase I study.

BACKGROUND: This study compared the pharmacokinetics (PK), immunogenicity, and safety of candidate tocilizumab biosimilar, CT-P47, administered via auto-injector (CT-P47 AI) or pre-filled syringe (CT-P47 PFS), in healthy Asian adults. RESEARCH DESIGN AND METHODS: In this phase I, multicenter, open-label study, participants were randomized 1:1 to receive a single 162 mg/0.9 mL dose of CT-P47 via AI or PFS. Primary endpoints were area under the concentration - time curve from time zero to infinity (AUC0-inf) and maximum serum concentration (Cmax). PK equivalence was determined if 90% confidence intervals (CIs) for the ratios of geometric least-squares means (gLSMs) were within the predefined 80-125% equivalence margin. Secondary PK parameters, immunogenicity, and safety outcomes were also assessed. RESULTS: Of 314 participants randomized (155 CT-P47 AI; 159 CT-P47 PFS), 310 received the study drug (153 CT-P47 AI; 157 CT-P47 PFS). Primary and secondary PK results, immunogenicity and safety were similar between groups. Ninety percent CIs for the ratio of gLSMs were within the predefined equivalence margin for AUC0-inf (85.87-102.94) and Cmax (82.98-98.16). CONCLUSIONS: PK equivalence between CT-P47 AI and CT-P47 PFS was demonstrated in healthy Asian adults, with comparable immunogenicity and safety between the two devices. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05617183.

Tocilizumab is a biologic medicine used to treat inflammatory diseases, such as rheumatoid arthritis. A biosimilar is a drug that is an almost identical copy of an approved original ('reference') biologic medicine; it has identical efficacy and safety to the original medicine but is typically less expensive. CT­P47 is in development as a possible tocilizumab biosimilar.Some patients prefer injections using an auto-injector (AI) rather than a pre-filled syringe (PFS), for reasons including ease of use and convenience. With an AI, medicine is delivered automatically by firmly pressing the device against the skin, whereas, with a PFS, a needle is inserted into the skin and medicine delivered by depressing the plunger. The injection of CT­P47 using a PFS has shown comparable pharmacokinetics (i.e., the uptake, metabolism and excretion of the drug by the body) and safety to tocilizumab. Therefore, if the pharmacokinetics and safety of CT­P47 administered via AI and PFS were shown to be similar, this might expand the choice of administration devices available to patients.In this study, 310 healthy adults received a single injection of CT­P47 via AI or PFS. Blood samples were taken over 43 days to analyze pharmacokinetics. The uptake, metabolism and elimination of CT­P47 by the body was similar when administered by each device, suggesting that CT­P47 can be administered by either AI or PFS.

Pharmacokinetics and safety of candidate tocilizumab biosimilar CT-P47 versus reference tocilizumab: a randomized, double-blind, single-dose phase I study.

BACKGROUND: CT-P47 is a candidate tocilizumab biosimilar. This study assessed the pharmacokinetic (PK) equivalence of CT-P47 and European Union-approved reference tocilizumab (EU-tocilizumab) in healthy Asian adults. RESEARCH DESIGN AND METHODS: This double-blind, multicenter, parallel-group trial randomized healthy adults (1:1) to receive a single (162 mg/0.9 mL) subcutaneous dose of CT-P47 or EU-tocilizumab. The primary endpoint (Part 2) was PK equivalence by area under the concentration - time curve (AUC) from time zero to last quantifiable concentration (AUC0-last), AUC from time zero to infinity (AUC0-inf), and maximum serum concentration (Cmax). PK equivalence was concluded if 90% confidence intervals (CIs) for the ratios of geometric least-squares means (gLSMs) were within the 80-125% equivalence margin. Additional PK endpoints, immunogenicity, and safety were evaluated. RESULTS: In Part 2, 289 participants were randomized (146 CT-P47; 143 EU-tocilizumab); 284 received study drug. AUC0-last, AUC0-inf, and Cmax were equivalent between CT-P47 and EU-tocilizumab: 90% CIs for the ratios of gLSMs were within the 80-125% equivalence margin. Secondary PK endpoints, immunogenicity, and safety were comparable between groups. CONCLUSIONS: CT-P47 demonstrated PK equivalence with EU-tocilizumab and was well tolerated, following a single dose in healthy adults. CLINICAL TRIAL REGISTRATION: www.clinicaltrials.gov identifier is NCT05188378.

Tocilizumab is a biologic medicine used to treat inflammatory diseases including rheumatoid arthritis. Biosimilars are drugs that are highly similar to an already approved, 'reference' biologic medicine. This means that they do not have any differences from the reference product in factors including structure, biologic function, efficacy, and safety, that might affect how well they work in patients. Biosimilars are often available at a lower cost than reference drugs, so their use can provide patients with better access to expensive treatments. There are no approved biosimilars of tocilizumab so far: CT-P47 is currently in development as a potential tocilizumab biosimilar.In the main part of this study, 289 healthy Asian volunteers were randomly allocated to receive a single injection of either CT-P47 or the reference drug, European Union-approved tocilizumab (EU-tocilizumab). The main aim of the study was to find out whether CT-P47 and EU-tocilizumab were equivalent in terms of pharmacokinetics (drug absorption, distribution, metabolism, and excretion by the body). This is part of a standard process required by regulatory authorities to ensure that biosimilars work as well as their reference drugs. Analysis of blood samples taken over 43 days showed that the pharmacokinetic profiles of CT-P47 and EU-tocilizumab were equivalent, after the volunteers received a single dose of either drug. Safety and immunogenicity (immune responses made to the drug) were also comparable between CT-P47 and EU-tocilizumab. While only healthy Asian adults were included, further research comparing CT-P47 with reference tocilizumab will help to ensure that the findings from the study can be applied to broader populations.

EEG-controlled tele-grasping for undefined objects.

This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions.

Path Planning for Multi-Arm Manipulators Using Deep Reinforcement Learning: Soft Actor-Critic with Hindsight Experience Replay.

Since path planning for multi-arm manipulators is a complicated high-dimensional problem, effective and fast path generation is not easy for the arbitrarily given start and goal locations of the end effector. Especially, when it comes to deep reinforcement learning-based path planning, high-dimensionality makes it difficult for existing reinforcement learning-based methods to have efficient exploration which is crucial for successful training. The recently proposed soft actor-critic (SAC) is well known to have good exploration ability due to the use of the entropy term in the objective function. Motivated by this, in this paper, a SAC-based path planning algorithm is proposed. The hindsight experience replay (HER) is also employed for sample efficiency and configuration space augmentation is used in order to deal with complicated configuration space of the multi-arms. To show the effectiveness of the proposed algorithm, both simulation and experiment results are given. By comparing with existing results, it is demonstrated that the proposed method outperforms the existing results.

A Randomized, Double-Blind Trial Comparing the Pharmacokinetics of CT-P16, a Candidate Bevacizumab Biosimilar, with its Reference Product in Healthy Adult Males.

BACKGROUND: CT-P16 is a candidate biosimilar of bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor that is used in the treatment of a range of advanced solid cancers. OBJECTIVE: The objective of this study was to demonstrate the pharmacokinetic equivalence of CT-P16 and European Union (EU)-approved bevacizumab (EU-bevacizumab) and US-licensed bevacizumab (US-bevacizumab) reference products. METHODS: In this double-blind, parallel-group phase I trial (ClinicalTrials.gov identifier NCT03247673), healthy adult males were randomized (1:1:1) to receive a single dose of CT-P16 5 mg/kg, EU-bevacizumab 5 mg/kg, or US-bevacizumab 5 mg/kg. Primary study endpoints were area under the concentration-time curve (AUC) from time zero to infinity (AUC∞), AUC from time zero to the last quantifiable concentration (AUClast), and maximum serum concentration (Cmax). Pharmacokinetic equivalence was shown if the 90% confidence intervals (CIs) of the geometric mean (GM) ratios of the AUC∞, AUClast, and Cmax were within the predefined bioequivalence margin of 80-125%. Safety and immunogenicity were also evaluated. RESULTS: A total of 144 subjects were randomized: 47 to CT-P16, 49 to EU-bevacizumab, and 48 to US-bevacizumab. The 90% CIs for the GM ratios of AUC∞, AUClast, and Cmax for CT-P16/EU-bevacizumab, CT-P16/US-bevacizumab, and EU-bevacizumab/US-bevacizumab comparisons were all within the bioequivalence margin. Mean serum concentration-time profiles, secondary pharmacokinetic parameters, and safety and immunogenicity profiles were comparable across all three treatment groups. CONCLUSION: CT-P16 demonstrated pharmacokinetic equivalence to EU-bevacizumab and US-bevacizumab. Safety and immunogenicity profiles were similar for CT-P16, EU-bevacizumab, and US-bevacizumab. These data support the further clinical evaluation of CT-P16 as a bevacizumab biosimilar. CLINICAL TRIALS REGISTRATION: NCT03247673.

Spatial uncertainty model for visual features using a Kinect™ sensor.

This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.