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Efficiency of nonparametric two-sample superiority tests based on restricted mean survival time under proportional hazards
No full textBackground
For randomized clinical trials with a time-to-event endpoint, proportional hazard models are typically used to estimate treatment effects and log-rank tests are commonly used for hypothesis testing. The summary measure of the primary estimand is frequently a hazard ratio. However, there is growing support for replacing this approach with a model-free summary measure and assumption-lean analysis method—a trend already observed for continuous and binary endpoints. One alternative is to base the analysis on the difference in restricted mean survival time (RMST) at a fixed timepoint. In a simple setting without covariates, an assumption-lean analysis can be achieved using nonparametric methods such as Kaplan-Meier estimation. The main advantage of moving to a model-free summary measure and assumption-lean analysis is that the interpretation of results no longer depends on the validity of the proportional hazards assumption. The potential disadvantage is that the nonparametric analysis may lose efficiency when the proportional hazards assumption holds. There is disagreement in recent literature on this issue, with some studies indicating similar efficiency between the two approaches, while others highlight significant advantages for proportional hazards models.
Methods
Existing asymptotic results are presented, and a simulation study is conducted to compare the efficiency of a proportional hazards analysis with a nonparametric analysis of the difference in RMST in a superiority trial. Previous studies have examined the effect of event rates on relative efficiency, as well as the impact of the censoring distribution separately. This investigation extends these findings by exploring the interactive effect of event rate and censoring distribution, helping to clarify the conflicting results from earlier research. Several illustrative examples are provided.
Results
In scenarios with high event rates and/or substantial censoring across a large proportion of the study window, and when both methods have access to the same amount of data, relative efficiency is close to unity. However, in cases with low or moderate event rates but when censoring is concentrated at the end of the study window, the proportional hazards analysis has a considerable efficiency advantage.
Conclusions
There are realistic combinations of event rates and censoring distributions where, if the proportional hazards assumption holds, the proportional hazards analysis is more efficient than a nonparametric RMST-based test. Additionally, the proportional hazards analysis can benefit from data collected beyond the restriction time. Therefore, it is inappropriate to assume that switching to a nonparametric RMST-based test would generally result in negligible efficiency loss, particularly when additional follow-up data is available but not used in the primary analysis. A key take-away from this study, is that the implications of requiring assumption-lean analysis methods should be carefully considered during the trial design phase
The Adoption and Use of Artificial Intelligence and Machine Learning in Clinical Development.
No full textThe use of artificial intelligence (AI) and machine learning (ML) in drug discovery has been well documented, but measures of levels of adoption, investments, and efficiencies gained from its use in clinical development have not yet been developed, captured or published. AI/ML use in clinical development is expected to increase, but its impact has not yet been systematically measured until now.The Tufts Center for the Study of Drug Development conducted a global online survey among pharmaceutical and biotechnology companies, contract research organizations (CROs), and data and technology vendors servicing drug developers. The survey gathered 302 responses assessing levels of AI/ML implementation across 36 distinct clinical trial planning and design, trial execution, and regulatory submission activities. The survey collected data on US dollar investment, time savings, and challenges and opportunities of AI/ML use in clinical development.Approximately one-third of the sample (36.9%) was not yet using or implementing AI/ML across 36 design and planning, execution, and regulatory submission activities; another 30.3% was beginning their AI/ML implementation (or piloting), 22.1% was partially implementing (or moving beyond pilots), and on average only 10.7% had fully implemented AI/ML (i.e., uses AI in most trials employing a repeatable process)
Streamlining enzyme discovery and development through data analysis and computation
No full textBiocatalysis, the use of Nature’s catalysts to perform chemical transformations on organic compounds, is a powerful tool in synthetic chemistry. In this context, the identification of enzymes which accept non-natural substrates is a key step to develop biocatalysts for anthropogenic applications. However, detecting enzymatic reaction products using analytical approaches such as LC-MS can be a complex task, especially when testing numerous putative substrates simultaneously. This complexity becomes even more prominent when evaluating CH-activating enzymes like Fe(II)/α-ketoglutarate dependent dioxygenases, which follow a radical reaction mechanism and are capable of following multiple reaction pathways leading to a variety of products. The complex nature of these reactions requires a data-driven strategy to detect both anticipated but also unexpected reaction outcomes, in this way leading to enhanced enzyme discovery and reaction pathway engineering capabilities
Future Directions in Drug-Drug Interaction Evaluations: Industry Perspective on the ICH M12 Guideline
No full textThe ICH M12 Guideline, adopted by the International Council for Harmonisation in 2024, provides a global framework for assessing drug-drug interaction (DDI) risks mediated by metabolic enzymes and drug transporters. The DDI Discussion Group in the International Consortium for Innovation and Quality identified key challenges across in vitro and clinical stages. In vitro challenges include accounting for protein binding, mitigating overestimations of DDI risks, and interpreting weak enzyme inhibition or induction effects. A case study explores cytochrome P450 (CYP) induction risks by major metabolites. The complexities of glucuronosyltransferase (UGT) and transporter inhibition or induction were contextualized. Clearance pathway evaluations for low turnover compounds and UGT or transporter substrates was also summarized for object DDIs. Clinically, challenges include the need for validated endogenous biomarkers to improve DDI risk assessments and finding alternatives to rifampin for CYP induction and Organic Anion Transporting polypeptide (OATP) inhibition due to nitrosamine contamination: reduced and non-selective induction by drugs like carbamazepine and phenytoin or OATP inhibition by cyclosporine. Further complexities involve therapeutic-protein DDIs, transporter-enzyme interplay and compounds acting as simultaneous inducers and time-dependent inhibitors. Addressing these gaps requires collaborative efforts to refine predictive models, improve in vitro-in vivo correlations, and enhance drug development and patient safety
An Eco-Friendly and Quality-by-Design Optimized Synchronous Spectrofluorescence Method for the Simultaneous Determination of Cleaning Residues of Anticancer Drugs Darolutamide and Enzalutamide From Manufacturing Surfaces
No full textA novel, sensitive, and eco-friendly
derivatization-free
synchronous fluorescence spectroscopic method was developed and optimized
for the simultaneous quantification of enzalutamide and darolutamide. A quality-by-
design
approach was adopted using
a screening design followed by Box–Behnken optimization to investigate the effects of photomultiplier tube voltage, solvent, excitation,
and emission slit width on fluorescence response. The determination of first-derivative
synchronous spectrofluorimetric
scan was done at Δλ = 50 nm, where amplitudes were recorded at 626 nm for darolutamide and 522 nm for enzalutamide without
any interference. The method was validated per ICH Q2(R2) guidelines, showing excellent linearity in ranges of 1.0–12.0 μg/mL
for enzalutamide and darolutamide with the LOQ value of < 1.0 μg/mL for both drugs. The validated method was successfully
applied to pharmaceutical formulations to determine cleaning residues of enzalutamide and darolutamide. The method was
applied at the lower level of 2.0 μg/mL for cleaning the residues from stainless-steel
surfaces in a manufacturing environment
with promising recovery results from rinse and swab methods. The method was evaluated for analytical greenness metrics using
Analytical Green Star Area and Multicolor Assessment tools. This study represents the first report of a synchronous fluorimetric
method for this drug pair and its usage in the pharmaceutical cleaning process
Utility of an in vitro lymphatics on-chip model for rank ordering subcutaneous absorption of monoclonal antibodies.
No full textThe lymphatic vasculature plays a key role in the subcutaneous absorption of macromolecules (>16 kDa). Recent trends toward subcutaneous delivery of macromolecular therapeutics have brought awareness to the need for preclinical estimation of subcutaneous bioavailability prior to first-in-human studies. In vitro tools offer a low-cost means to inform molecule design and formulation and mitigate costly mistakes of under- or overestimation of therapeutic dose and exposure in clinical studies. Building on a previous engineered on-chip lymphatics platform, the utility of an in vitro model to rank therapeutic proteins based on lymphatic absorption was investigated. Lymphatics grown under a combination of interstitial flow and growth factor supplementation on-chip demonstrated in vivo-like morphology, phenotypic marker expression, and solute drainage rates after a 4-day culture period. Dextrans of increasing molecular weight were assessed on the model and demonstrated an inverse relationship between size and diffusion coefficient. Similarly, a reduced lymphatic transport on-chip was observed for large antibody aggregates compared to non-aggregated molecules. More importantly, lymphatic transport of a panel of nine therapeutic proteins and monoclonal antibodies successfully rank ordered these molecules based on their subcutaneous bioavailability in humans (Pearson r = 0.8929). The on-chip lymphatics model described here appears as a promising tool for rank ordering subcutaneous lymphatic absorption during early drug development to increase the potential for successful candidate selection moving toward the clinic
MISO: microfluidic protein isolation enables single-particle cryo-EM structure determination from a single cell colony.
No full textSingle-particle cryogenic electron microscopy (cryo-EM) enables reconstruction of atomic-resolution 3D maps of proteins by visualizing thousands to millions of purified protein particles embedded in vitreous ice. This corresponds to picograms of purified protein, which can potentially be isolated from a few thousand cells. Hence, cryo-EM holds the potential of a very sensitive analytical method for delivering high-resolution protein structure as a readout. In practice, millions of times more starting biological material is required to prepare cryo-EM grids. Here we show that using a micro isolation (MISO) method, which combines microfluidics-based protein purification with cryo-EM grid preparation, cryo-EM structures of soluble bacterial and eukaryotic membrane proteins can be solved starting from less than 1 µg of a target protein and progressing from cells to cryo-EM grids within a few hours. This scales down the amount of starting biological material hundreds to thousands of times, opening possibilities for the structural characterization of hitherto inaccessible proteins
Patient-Centric Endotoxin Acceptance Criteria
No full textSummary:
This document discusses the industry's opinion on endotoxin acceptance criteria for parenteral drug products, emphasizing the need for patient-centric criteria based on average body weight and the threshold pyrogenic dose of 5 EU/kg/hr. It highlights the inconsistency between regulatory expectations and compendial guidelines, including recent trends to tighten acceptance criteria using the lowest body weight or safety factors. The document argues that overly strict criteria can risk supply consistency and limit future process improvements. It recommends calculating endotoxin contributions from diluent and co-administered drugs using product-specific calculations or a blanket safety factor. The analysis of historical data from FDA observations, product recalls, and adverse event reports demonstrates that the current industry practices provide significant safety margins. The conclusion is that the use of average body weight for calculating endotoxin acceptance criteria is scientifically justified, ensuring patient safety and manufacturing efficiency
Proof of a successful decontamination process with H2O2
No full textThe use of isolators in the manufacture and quality control of sterile medicinal products has been a trend for years and has increased significantly as a result of Annex 1 of the EC GMP guidelines, which explicitly recommends the use of barrier systems. Isolators are unbeatable when it comes to effectively preventing extrinsic contamination and therefore make a significant contribution to drug safety. The core process in the application of isolator technology is fully automated decontamination, which can be carried out using various methods. As different as the methods are, they are almost all based on the same active principle, the evaporation of liquid to gaseous hydrogen peroxide, which has proven to be the most suitable decontamination agent. To check the decontamination effect and thus the decontamination success of the system, tests are carried out throughout the life cycle of the system [1;2]. Regardless of the life-cycle stage (e.g. qualification, cycle development or re-qualification), different types of indicators are used to prove the system's performance. These indicators can be divided into chemical, biological and enzymatic indicators. They can be used individually, but their combined use is not only more meaningful, but also allows more far-reaching conclusions to be drawn
Graphitic carbon nitride/nickel dual catalysis for decarboxylative synthesis of unsymmetrical ketones from keto acids
No full textThe emergence of photoredox catalysis in synthetic chemistry has brought a plethora of new synthetic methodologies to the modern chemist’s toolbox, enabling a range of novel synthetic disconnections. In particular, metallaphotoredox chemistry, the merger of transition-metal catalysis and photoredox catalysis, has allowed the novel synthesis of previously elusive molecular scaffolds and the utilisation of a wide variety of potential coupling partners. In an effort to expand upon our earlier work, we investigated the use of α-keto carboxylic acids as a source of acyl radicals with a commercial gCN photocatalyst, furnishing ketones after nickel-catalysed coupling with aryl halides, avoiding the use of iridium-based photocatalysts