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Author Correction: Bipotent transitional liver progenitor cells contribute to liver regeneration.
No full textFollowing severe liver injury, when hepatocyte-mediated regeneration is impaired, biliary epithelial cells (BECs) can transdifferentiate into functional hepatocytes. However, the subset of BECs with such facultative tissue stem cell potential, as well as the mechanisms enabling transdifferentiation, remains elusive. Here we identify a transitional liver progenitor cell (TLPC), which originates from BECs and differentiates into hepatocytes during regeneration from severe liver injury. By applying a dual genetic lineage tracing approach, we specifically labeled TLPCs and found that they are bipotent, as they either differentiate into hepatocytes or re-adopt BEC fate. Mechanistically, Notch and Wnt/β-catenin signaling orchestrate BEC-to-TLPC and TLPC-to-hepatocyte conversions, respectively. Together, our study provides functional and mechanistic insights into transdifferentiation-assisted liver regeneration
Assessing the utility of common arguments used in expert review of in silico predictions as part of ICH M7 assessments
No full textExpert review of two predictions, made by complementary (quantitative) structure-activity relationship (Q)SAR models, to an overall conclusion is a key component of using in silico tools to assess the mutagenic potential of impurities as part of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 (R1) guideline. In lieu of a specified protocol, numerous publications have presented best practise guides, often indicating the occurrence of common prediction scenarios and the evidence required to resolve them. A semi-automated expert review tool has been implemented in Lhasa Limited’s Nexus platform following collation of these common arguments and assignment to the associated prediction scenarios made by Derek Nexus and Sarah Nexus. Using datasets primarily donated by pharmaceutical companies, an automated analysis of the frequency these prediction scenarios occur, and the likelihood of the associated arguments assigning the correct resolution, could then be conducted. This article highlights that a relatively small number of common arguments may be used to accurately resolve many prediction scenarios to a single conclusion. The use of a standardised method of argumentation and assessment of evidence for a given impurity is proposed to improve the efficiency and consistency of expert review as part of an ICH M7 submission
High-throughput synthesis provides data for predicting molecular properties and reaction success.
No full textThe generation of attractive scaffolds for drug discovery efforts requires the expeditious synthesis of diverse analogues from readily available building blocks. This endeavor necessitates a trade-off between diversity and ease of access and is further complicated by uncertainty about the synthesizability and pharmacokinetic properties of the resulting compounds. Here, we document a platform that leverages photocatalytic N-heterocycle synthesis, high-throughput experimentation, automated purification, and physicochemical assays on 1152 discrete reactions. Together, the data generated allow rational predictions of the synthesizability of stereochemically diverse C-substituted N-saturated heterocycles with deep learning and reveal unexpected trends on the relationship between structure and properties. This study exemplifies how organic chemists can exploit state-of-the-art technologies to markedly increase throughput and confidence in the preparation of drug-like molecules
Rare oncology therapeutics: review of clinical pharmacology package of drug approvals (2019-2023) by US FDA, best practices and recommendations.
No full textThere are many challenges with rare diseases drug development and rare oncology indications are not different. To understand the regulatory landscape as it relates to application of clinical pharmacology principles in rare oncology product development, we reviewed publicly available information of 39 approvals by US FDA between January 2019 and March 2023. The objective was to understand the expected clinical pharmacology studies and knowledge base in such approvals. Model informed drug development (MIDD) applications were also reviewed, as such approaches are expected to play a critical role in filling clinical pharmacology gaps in rare oncology, where number of clinical trials and size of these trials will perhaps continue to be small. The findings highlighted how clinical pharmacology contributed to the evidence of effectiveness, dose optimization and elucidation of intrinsic and extrinsic factors affecting drug's behavior. Clinical pharmacology studies were often integrated with modeling in many of the NDAs/BLAs. Of the post marketing requirements (PMR) received, 18% were for dose optimization, 49% for DDI, 8% for QTc, 49% for specific population, and 5% for food effect. Two post marketing commitments (PMC) were issued for immunogenicity of the 11 biologics submissions. 15% (6 of 39) of the submissions used maximum tolerated dose (MTD) to advance their molecule into Phase 2 studies. Of them 3 approvals received PMR for dose optimization. 3 + 3 was the most prevalent Phase 1 design with use in 74% of the New Drug Applications (NDA)/Biologic License Applications (BLA) reviewed. Rest used innovative approaches such as BLRM, BOIN or mTPi, with BLRM being the most common. Seamless clinical pharmacology and MIDD approaches are paramount for rare oncology drug development
Machine intelligence models for fast, quantum mechanics-based approximation of drug lipophilicity
No full textLipophilicity, as measured by the partition coefficient between octanol and water (log P), is a key parameter in early drug discovery research. However, measuring log P experimentally is difficult for specific compounds and log P ranges. The resulting lack of reliable experimental data impedes development of accurate in silico models for such compounds. In discovery projects at Novartis focused on such compounds, a quantum mechanics (QM) based tool for log P estimation has emerged as a useful supplement to experimental measurements and as a preferred alternative to existing empirical models. However, this QM-based approach incurs substantial computational cost, limiting its applicability to smaller series and prohibiting quick, interactive ideation. This work explores a set of machine intelligence models (Random Forest, Lasso, XGBoost, Chemprop, and Chemprop3D) to learn calculated log P values on both a public and an in-house dataset to obtain a computationally affordable, QM-based estimation of drug lipophilicity. Chemprop emerges as the best-performing model with mean absolute errors of 0.44 and 0.33 log units for scaffold split test sets of the public and in-house dataset, respectively. Analysis of learning curves suggests that a further decrease in test set error can be achieved by increasing the training set size. We discuss advantages of using synthetic data and the impact of dataset splitting strategy and gain insights into model failure modes. Potential use cases for the presented models include pre-screening of large compound collections and prioritization of compounds for full QM calculations
Editorial for "The effects of respiratory muscle training on resting state brain activity and thoracic mobility in healthy subjects: a randomized controlled trial”
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Neurofilament light chain and dorsal root ganglia injury after adeno-associated virus 9 gene therapy in nonhuman primates.
No full textIn nonhuman primates (NHPs), adeno-associated virus serotype 9 (AAV9) vectorized gene therapy can cause asymptomatic microscopic injury to dorsal root ganglia (DRG) and trigeminal ganglia (TG) somatosensory neurons, causing neurofilament light chain (NfL) to diffuse into cerebrospinal fluid (CSF) and blood. Data from 260 cynomolgus macaques administered vehicle or AAV9 vectors (intrathecally or intravenously) were analyzed to investigate NfL as a soluble biomarker for monitoring DRG/TG microscopic findings. The incidence of key DRG/TG findings with AAV9 vectors was 78% (maximum histopathology severity, moderate) at 2-12 weeks after the dose. When examined up to 52 weeks after the dose, the incidence was 42% (maximum histopathology severity, minimal). Terminal NfL concentrations in plasma, serum, and CSF correlated with microscopic severity. After 52 weeks, NfL returned to pre-dose baseline concentrations, correlating with microscopic findings of lesser incidence and/or severity compared with interim time points. Blood and CSF NfL concentrations correlated with asymptomatic DRG/TG injury, suggesting that monitoring serum and plasma concentrations is as useful for assessment as more invasive CSF sampling. Longitudinal assessment of NfL concentrations related to microscopic findings associated with AAV9 administration in NHPs indicates NfL could be a useful biomarker in nonclinical toxicity testing. Caution should be applied for any translation to humans
COMPARATIVE ANALYSIS OF POROSITY MEASUREMENT TECHNIQUES USING PHARMACEUTICAL MATERIALS
No full textRoller compaction or dry granulation is one of the techniques used to improve the flow properties of pharmaceutical materials where direct compaction of tablets is not possible. It is often preferred over wet granulation due to faster processing times, handling moisture sensitive compounds and lower energy consumption. Ribbons are produced during roller compaction and ribbon porosity is considered a critical intermediate attribute. Ribbon porosity measurements are often used to scale-up, transfer processes and validate roller compactor modelling and simulations. Various ribbon porosity measurement techniques exist, each with it is own advantages and challenges. The most used techniques in the pharmaceutical industry for ribbon porosity measurements are envelope volume using the Geopyc technique, mercury porosimeter and X-ray Microtomography. However, there are ongoing research activities to find innovative techniques which are simple, faster, non-destructive, precise and accurate. In this study, the Laser triangulation technique is used for the evaluation of the ribbon porosity and results are compared with the commonly used technique for comparison of the results and its suitability as an at-site measurement technique. In the initial experiments, riblets were manufactured using a Stylone compaction simulator using Microcrystalline Cellulose (MCC) as the model excipient. In this investigation, ribbons were produced using commercially available roller compactors namely Gerteis Minipactor and Bepex Pharmapactor. Ribbons were manufactured using a roller compactor using MCC for further evaluation of the techniques. Experimental compound A was used in the active formulation and further studies were carried out in pilot and launch scales to generate ribbons for further comparison of the technique and assess the suitability of each measuring technique to quantify the porosity data. This paper discusses in detail the importance of the roller compaction process and ribbon porosity as critical intermediate material attributes, different porosity measurement techniques, results obtained and comparative analysis of the data generated
Use of Endogenous Biomarkers to Guide OATP1B Drug-Drug Interaction Risk Assessment: Evaluation by the Pharmaceutical Industry
No full textDrug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptides 1B1/1B3 (OATP1B) can be substantial and clinically relevant, however challenges remain for predicting these DDIs using in vitro inhibition data. Emerging evidence suggests the use of endogenous biomarkers, particularly coproporphyrin-I (CP-I), as selective markers of in vivo OATP1B activity. The present work under the International Consortium for Innovation and Quality in Pharmaceutical Development was aimed primarily at establishing the relationship between changes in CP-I exposure and substrate drug exposure following clinical OATP1B inhibition. Additionally, we evaluated static models to predict changes in exposure of CP-I, as a selective OATP1B endogenous substrate. Literature and proprietary data related to clinical OATP1B biomarkers along with pertinent in vitro and clinical DDI information were collected to identify clinical DDIs via primarily OATP1B inhibition and assess the relationship between substrate drug and CP-I exposure changes. Significant correlations were observed between CP-I area-under-the-curve ratio (AUCR) or maximum concentration ratio (CmaxR) and AUCR of substrate drugs. CP-I AUCR and CmaxR of <1.25 was associated with negative OATP1B-mediated DDIs (AUCR <1.25) with no false negative predictions observed while applying both criteria. CP-I AUCR of <1.5 and CmaxR of <2 was associated with OATP1B-mediated DDIs with AUCR <2. A correlation was identified between CP-I exposure changes and OATP1B1 static DDI predictions. Recommendations for collecting and interpreting CP-I data are described, including a decision tree for guiding DDI risk assessment. Measurement of CP-I is considered sufficient for evaluation of in vivo OATP1B inhibition potential
Quantitative Assessment of Ribociclib Exposure-Response Relationship to Justify Dose Regimen in Patients with Advanced Breast Cancer.
No full textRibociclib in combination with endocrine therapy (ET) is a globally approved treatment option for patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) and has demonstrated significantly improved overall survival (OS) in 3 phase 3 clinical trials. To justify the dose regimen and dose modification scheme for patients with ABC, the pharmacokinetic (PK), safety, and efficacy data of ribociclib were analyzed. The data of several phase 1-3 clinical studies were pooled and analyzed to characterize the relationship between exposure (dose or PK) and efficacy (progression-free survival (PFS), time to response, and OS) or safety (neutropenia and QT interval prolongation). The exposure-efficacy analysis showed no apparent relationship between ribociclib exposure and efficacy (PFS and OS), and efficacy analysis by dose reduction showed that patients with ABC continued to benefit from the treatment following dose reduction, supporting the starting dose of 600 mg as well as dose reductions to 400 and 200 mg. The exposure-safety analysis showed that neutropenia and QT prolongation are related to ribociclib exposure that can be effectively managed by individualized dose modification (dose reduction/interruption). Collective evidence from the exposure-response analyses for efficacy and safety support the use of ribociclib in combination with ET partners at the starting dose of 600 mg, and also the effectiveness of individualized dose reductions in managing safety, while maintaining efficacy, in patients with HR+/HER2- ABC. This analysis illustrates the utility of quantitative assessment in justifying dose selection and dose modification for oncology medicines