Automated online deconjugation of antibody-drug conjugate for small molecule drug profiling.

Antibody-drug conjugates (ADCs) are designed by chemically linking highly potent cytotoxic small molecule drugs to monoclonal antibodies of unique specificity for targeted destruction of cancer cells. This innovative class of molecules incurs unique developmental challenges due to its structural complexity of having both small molecule and protein components. The stability of the small molecule payload on the ADC is a critical attribute as it directly relates to product efficacy and patient safety. This study describes the use of an end-to-end automated workflow for effective and robust characterization of the small molecule drug while it is conjugated to the antibody. In this approach, online deconjugation was accomplished by an autosampler user defined program and 1D size exclusion chromatography was utilized to provide separation between small molecule and protein species. The small molecule portion was then trapped and sent to the 2D for separation and quantification by reversed-phase liquid chromatography with identification of impurities and degradants by mass spectrometry. The feasibility of this system was demonstrated on an ADC with a disulfide-based linker. This fully automated approach avoids tedious sample preparation that may lead to sample loss and large assay variability. Under optimized conditions, the method was shown to have excellent specificity, sensitivity (LOD of 0.036 µg/mL and LOQ of 0.144 µg/mL), linearity (0.04-72.1 µg/mL), precision (system precision %RSD of 1.7 and method precision %RSD of 3.4), accuracy (97.4 % recovery), stability-indicating nature, and was successfully exploited to analyze the small molecule drug on a panel of stressed ADC samples. Overall, the workflow established here offers a powerful analytical tool for profiling the in-situ properties of small molecule drugs conjugated to antibodies and the obtained information could be of great significance for guiding process/formulation development and understanding pharmacokinetic/pharmacodynamic behavior of ADCs.

Development of a Near-Infrared Spectroscopy (NIRS)-Based Characterization Approach for Inherent Powder Blend Heterogeneity in Direct Compression Formulations.

With the advent of continuous direct compression (CDC) process, it becomes increasingly desirable to characterize inherent powder blend heterogeneity at a small batch scale for a robust and CDC-amenable formulation. To accomplish this goal, a near infrared spectroscopy (NIRS)-based characterization approach was developed and implemented on multiple direct compression (DC) blends in this study, with the intended purpose of complementing existing formulation development tools and enabling to build an early CMC data package for late-phased process analytical technology (PAT) method development. Three fumaric acid DC blends, designed to harbor varied degrees of inherent blend heterogeneity, were employed. Near infrared spectral data were collected on a kg-scale batch blender via both time- and angle-based triggering modes. The time-triggered data were used to investigate the blending heterogeneity with respect to rotation angles, while the angle-triggered data were used to provide blending variability characterization and compare against off-line HPLC-based results. The time-triggered data revealed that the greatest blend variability was observed between revolutions, while the blending variability within a single revolution stayed relatively low with respect to rotation angles. This confirmed earlier literature findings that the bottom layer of powder blends tends to move with the blender within each revolution, and the most intense powder mixing takes place across revolutions. This also indicates the use of blending speed and the number of co-adds are not able to increase sampling volume to improve signal-to-noise ratio under a tumble-bin blender as what were typically done in a feedframe application. The angle-triggered data showed that there is a consistent trend between NIRS and HPLC-based methods on characterizing blend heterogeneity across the blends at a given sample size. This study contributes to establishing NIRS as a potential characterization approach for inherent powder blend heterogeneity for early R&D. It also highlights the promise of continuous characterization of inherent powder blend heterogeneity from gram scale to mini-batch CDC scale.

Corrigendum to "Mixed methods feasibility study for the surviving opioid overdose with naloxone education and resuscitation (SOONER) trial" [Resuscitation Plus 6 (2021) 100131].

[This corrects the article DOI: 10.1016/j.resplu.2021.100131.].

Mixed methods feasibility study for the surviving opioid overdose with naloxone education and resuscitation (SOONER) trial.

AIM: We plan to conduct a randomised clinical trial among people likely to witness opioid overdose to compare the educational effectiveness of point-of-care naloxone distribution with best-available care, by observing participants' resuscitation skills in a simulated overdose. This mixed methods feasibility study aims to assess the effectiveness of recruitment and retention strategies and acceptability of study procedures. METHODS: We implemented candidate-driven recruitment strategies with verbal consent and destigmatizing study materials in a family practice, emergency department, and addictions service. People ≥16 years of age who are likely to witness overdose were randomized to point-of-care naloxone distribution or referral to an existing program. We evaluated participant skills as a responder to a simulated overdose 3-14 days post-recruitment. Retention strategies included flexible scheduling, reminders, cash compensation and refreshments. The primary outcome was recruitment and retention feasibility, defined as the ability to recruit 28 eligible participants in 28 days, with <50% attrition at the outcome simulation. Acceptability of study procedures and motivations for participation were assessed in a semi-structured interview. RESULTS: We enrolled 30 participants over 24 days, and retained 21 participants (70%, 95%CI 56.7-100). The most common motivation for participation was a desire to serve the community or loved ones in distress. Participants reported that study procedures were acceptable and that the outcome simulation provided a supportive and affirming environment. CONCLUSION: The planned trial is ready for implementation. Recruitment and retention is feasible and study processes are acceptable for people who are likely to witness overdose. (Registration: NCT03821649).

Clinical Characteristics and Remedy Profiles of Patients with COVID-19: A Retrospective Cohort Study.

OBJECTIVE: The aim of the study was to identify indicated homeopathic remedies based on the clinical characteristics of coronavirus disease 2019 (COVID-19) patients in India. METHODS: In this retrospective, cohort study, confirmed COVID-19 patients admitted at a COVID Health Centre in New Delhi between April 29 and June 17, 2020 were given conventional and homeopathic treatment. Patients were grouped into mild, moderate or severe categories of disease. Their symptomatologic profiles were analyzed to identify indicated homeopathic medicines. RESULTS: A total of 196 COVID-19 patients were admitted. One hundred and seventy-eight patients had mild symptoms; eighteen patients had moderate symptoms; no patients with severe symptoms were included as they were referred to tertiary care centers with ventilatory support. The mean age of patients with mild symptoms was significantly lower (38.6 years; standard deviation or SD ± 15.8) compared with patients in the moderate category (66.0 years; SD ± 9.09). The most important symptoms identified were fever (43.4%), cough (47.4%), sore throat (29.6%), headache (18.4%), myalgia (17.9%), fatigue (16.8%), chest discomfort (13.8%), chills (12.6%), shortness of breath (11.2%) and loss of taste (10.2%). Twenty-eight homeopathic medicines were prescribed, the most frequently indicated being Bryonia alba (33.3%), Arsenicum album (18.1%), Pulsatilla nigricans (13.8%), Nux vomica (8%), Rhus toxicodendron (7.2%) and Gelsemium sempervirens (5.8%), in 30C potency. CONCLUSION: Data from the current study reveal that Arsenicum album, Bryonia alba, Pulsatilla nigricans, Nux vomica, Rhus toxicodendron and Gelsemium sempervirens are the most frequently indicated homeopathic medicines. A randomized controlled clinical trial based on this finding is the next step.

Ideals of the Multiview Variety.

The multiview variety of an arrangement of cameras is the Zariski closure of the images of world points in the cameras. The prime vanishing ideal of this complex projective variety is called the multiview ideal. We show that the bifocal and trifocal polynomials from the cameras generate the multiview ideal when the foci are distinct. In the computer vision literature, many sets of (determinantal) polynomials have been proposed to describe the multiview variety. We establish precise algebraic relationships between the multiview ideal and these various ideals. When the camera foci are noncoplanar, we prove that the ideal of bifocal polynomials saturate to give the multiview ideal. Finally, we prove that all the ideals we consider coincide when dehomogenized, to cut out the space of finite images.

Simultaneous quantitation of water and residual solvents in pharmaceuticals by rapid headspace gas chromatography with thermal conductivity detection (GC-TCD).

In the pharmaceutical industry, an array of analytical testing is performed to demonstrate the safety and efficacy of drug substance and drug products. Among the most critical attributes of release testing are quantitation of residual solvents from the manufacturing process, which pose toxicity concerns, and determination of water content, which can impact potency and shelf life. Residual solvent determination in pharmaceuticals is most commonly performed using headspace capillary gas chromatography (GC) with flame ionization detection (FID), a robust technique that incorporates a mode of detection noteworthy for its sensitivity and wide dynamic range. However, FID responds exclusively to combustible organic species, and does not produce any signal for common gases such as carbon dioxide, ammonia, and notably water. While thermal conductivity detection (TCD) is an alternate, universal mode of detection that has a known response to all GC-appropriate compounds, including water, its use among pharmaceutical companies is uncommon due to the ubiquity of the more sensitive FID and the availability of other techniques for water quantitation such as Karl Fischer titrations (KF). In this work, the use of headspace GC-TCD was successfully demonstrated for the development of a 7.5-minute method for simultaneous quantitation of water, over 25 common residual solvents, and other volatile impurities in small molecule pharmaceutical samples. By carefully controlling sample preparation to minimize the impact of residual water from the diluent, the results for residual solvents and water obtained by this technique were found to be comparable to those of GC-FID and KF, respectively. Headspace GC-TCD improves the throughput of drug testing by greatly reducing the need for KF testing and associated expensive reagents, and helps to conserve samples that are often limited in early stages of development. The technique has desired sensitivity, precision, accuracy and linear dynamic range suitable for pharmaceutical analysis.