Xenobiotica最新文献

1. Antibody-drug conjugates (ADCs) are an important class of cancer therapies. They are complex molecules, comprising an antibody, a cytotoxic payload, and a linker. ADCs intend to confer high specificity by targeting a unique antigen expressed predominately on the surface of the tumour cells than on the normal cells and by releasing the potent cytotoxic drug inside the tumour causing cytotoxic cell death. Despite high specificity to tumour antigens, many ADCs are associated with off-target and on-target off-tumour toxicities, often leading to safety concerns before achieving the desirable clinical efficacy. Therefore, it is crucial to improve the therapeutic index (TI) of ADCs to enable the full potential of this important therapeutic modality. 2. The review summarises current approaches to improve the translation of safety, pharmacokinetics, and TI of ADCs. Common safety findings of ADCs resulting from off-target and on-target toxicities and nonclinical approaches to de-risk ADC safety will be discussed; multiple approaches of using preclinical and clinical dose and exposure data to calculate TI to guide clinical dosing will be elaborated; different approaches to improve TI of ADCs, including selecting the right target, right payload-linker and patients, optimising physicochemical properties, and using fractionation dosing, will also be discussed.

Stable isotope labelling by amino acids in cell culture (SILAC) is an established technique used in quantitative mass spectrometry (MS)-based proteomics. SILAC is also used to generate stable isotope labelled (SIL) antibodies for internal standards (IS) used in LC-MS/MS bioassays to improve quantitative robustness.Total antibody (TAb) is measured to evaluate pharmacokinetics (PK) of antibody drug conjugate (ADC) candidates measured by either ligand binding (LBA) or LC-MS/MS. Herein, we describe an application of SILAC, where multiple SIL combinations of an antibody are used for cassette dosing and PK evaluation.Our preclinical studies demonstrate SILAC-labelled ADC therapeutics did not alter antibody PK. Furthermore, with cassette dosing SIL antibodies exhibited comparable exposure to discretely administered unlabelled test articles in rats.In addition, SIL antibodies were conjugated to cytotoxic payloads to create SIL ADCs and cassette dosed in a cynomolgus monkey PK study and SIL ADCs yielded comparable PK results to discrete dosed unlabelled ADCs.In conclusion, SIL antibodies used with a cassette dosing strategy increases PK screening throughput of ADC candidates in preclinical species. Additionally, cassette dosing strategy further facilitates the responsible use of laboratory animals to achieve the three-Rs (Replacement, Reduction, and Refinement).

Native liquid chromatography mass spectrometry (LC-MS) is a commonly used approach for intact analysis of inter-chain cysteine conjugated antibody-drug conjugates (ADCs). Coupling native LC-MS with affinity capture provides a platform for intact ADC analysis from in vivo samples and characterisation of individual drug load species, specifically the impact of drug linker deconjugation, hydrolysis, and differential clearance in a biological system.This manuscript describes data generated from native LC-MS analysis of ADCs from human plasma, both in vitro incubations and clinical samples. It also details the pharmacokinetic (PK) model built to specifically characterise the disposition of individual drug load species from MMAE and MMAF interchain cysteine conjugated ADCs.In vitro deconjugation and hydrolysis rates were similar across both ADCs. Differential clearance of higher loaded species in vivo was pronounced for the MMAE conjugated ADC, while systemic elimination after accounting for deconjugation was similar across drug loads for the MMAF conjugated ADC. This is the first report of affinity capture native LC-MS analysis, and subsequent modelling of deconjugation, hydrolysis and clearance rates of individual drug load species using clinical data from cysteine conjugated ADCs.

Polyethylene glycol (PEG) was introduced into synthetic bilirubin 3α and a PEGylated bilirubin 3α nanoparticle (BX-001N, Brixelle®) was developed for the first time.An in vitro microsomal stability study, in vivo PK studies with intravenous bolus (IV) and subcutaneous injection (SC), and a semi-mass balance study of BX-001N were investigated to evaluate its pharmacokinetic (PK) properties in male Sprague-Dawley (SD) rats using developed liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-qTOF/MS).Following IV administration at 10 or 30 mg/kg, BX-001N showed very low clearance (0.33-0.67 mL/min/kg) with predominant distribution in the vascular system (Vd = 51.73-83.02 mL/kg). BX-001N was also very stable in vitro liver microsomal stability study.Following SC administration at 10 or 30 mg/kg, the bioavailability of BX-001N in plasma at 10 mg/kg was around 43% and showed the less dose-proportionality at 30 mg/kg dose.BX-001N was mainly excreted via the urinary pathway (86.59-92.99% of total amount of parent drug in excreta; urine and faeces) not via the biliary one.

Antibody-drug conjugates (ADCs) are a class of biopharmaceuticals that combine the specificity of monoclonal antibodies (mAbs) with the cytotoxicity of small molecule drugs. 15 ADCs have been approved by regulatory authorities up to now, mainly for indications in oncology, however, this review paper will only focus on the 13 ADCs that have been approved by either the FDA or EMA.ADME (Absorption, Distribution, Metabolism, and Excretion) studies are essential for the development of small molecule drugs to evaluate their disposition properties. These studies help to select drug candidates, determine the optimal dosing regimen and help to identify potential safety concerns for the drug of interest in human. Tissue distribution studies are also important as they facilitate the understanding of the efficacy and safety for parent drug and its metabolites in preclinical and clinical studies.For biologics, ADME studies are usually not required. In this paper, we review the existing approval packages and literature for approved ADCs to determine the extent of ADME studies performed as part of ADC registration packages.We conclude that ADME studies are recommended for the development of ADCs if new linkers and payloads are used that have never been used in humans before as these studies provide valuable information on the pharmacokinetic properties, optimal dosing regimen, and potential safety concerns. However, for the development of ADCs with established linker payload combinations, radiolabelled ADME studies may not be necessary if the distribution, metabolism and excretion properties have been described before. Clinical radiolabelled ADME studies are not recommended where patients are treated for life threating diseases like for indications in oncology.

Over the past two decades, antibody-drug conjugates (ADCs) have emerged as a highly effective drug delivery technology. ADCs utilise a monoclonal antibody, a chemical linker, and a therapeutic payload to selectively deliver highly potent pharmaceutical agents to specific cell types.Challenges such as premature linker cleavage and clearance due to linker hydrophobicity have adversely impacted the stability and safety of ADCs. While there are various solutions to these challenges, our team has focused on replacement of hydrophobic ValCit linkers (cleaved by CatB) with Asn-containing linkers that are cleaved by lysosomal legumain.Legumain is abundantly present in lysosomes and is known to play a role in tumour microenvironment dynamics. Herein, we directly compare the lysosomal cleavage, cytotoxicity, plasma stability, and efficacy of a traditional cathepsin-cleavable ADC to a matched Asn-containing legumain-cleavable ADC.We demonstrate that Asn-containing linker sequences are specifically cleaved by lysosomal legumain and that Asn-linked MMAE ADCs are broadly active against a variety of tumours, even those with low legumain expression. Finally, we show that AsnAsn-linked ADCs exhibit comparable or improved efficacy to traditional ValCit-linked ADCs. Our study paves the way for replacement of the traditional ValCit linker technology with more hydrophilic Asn-containing peptide linker sequences.

1. Antibody-drug conjugates (ADCs) represent an advanced category of biotherapeutic agents, typically consisting of an antibody bound to a biologically-active cytotoxic agent. Since the first ADC, Mylotarg^TM, was approved in 2000, there have been fifteen ADCs sanctioned to date, with thirteen receiving approval from the FDA for the treatment of a variety of cancers, including blood malignancies and solid tumors.

2. In this Special Issue of Xenobiotica focusing on ADCs, our goal is to compile a collection of papers, featuring both original research and review articles authored by specialists in academia and the pharmaceutical industry, to showcase some of the historical insights gained, current progress, and future prospects to enhance comprehension and tackle obstacles in the field of ADC development for cancer therapy.

3. This special issue features articles that evaluate key components of ADC development, including payload design, innovative linker chemistries, and the use of new technologies for site-specific conjugations beyond traditional engineered cysteines. It also spotlights cutting-edge ADC structures like bispecific ADCs, dual-payload ADCs, targeted nanoparticles and antibody oligonucleotide conjugates (AOCs).

4. Several other papers discuss bioanalytical and ADME strategies for ADCs as well. In addition, approaches to improve the translation of pharmacokinetics, safety, and therapeutic index (TI) of ADCs are presented.

Unexpected metabolism could lead to the failure of many late-stage drug candidates or even the withdrawal of approved drugs. Thus, it is critical to predict and study the dominant routes of metabolism in the early stages of research.We describe the development and validation of a 'WhichEnzyme' model that accurately predicts the enzyme families most likely to be responsible for a drug-like molecule's metabolism. Furthermore, we combine this model with our previously published regioselectivity models for Cytochromes P450, Aldehyde Oxidases, Flavin-containing Monooxygenases, UDP-glucuronosyltransferases and Sulfotransferases - the most important Phase I and Phase II drug metabolising enzymes - and a 'WhichP450' model that predicts the Cytochrome P450 isoform(s) responsible for a compound's metabolism.The regioselectivity models are based on a mechanistic understanding of these enzymes' actions and use quantum mechanical simulations with machine learning methods to accurately predict sites of metabolism and the resulting metabolites. We train heuristics based on the outputs of the 'WhichEnzyme', 'WhichP450', and regioselectivity models to determine the most likely routes of metabolism and metabolites to be observed experimentally.Finally, we demonstrate that this combination delivers high sensitivity in identifying experimentally reported metabolites and higher precision than other methods for predicting in vivo metabolite profiles.

The selection of appropriate starting dose and suitable method to predict an efficacious dose for novel oncology drug in the early clinical development stage poses significant challenges. The traditional methods of using body surface area transformation from toxicology studies to predict the first-in human (FIH) starting dose, or simply selecting the maximum tolerated dose (MTD) or maximum administered dose (MAD) as efficacious dose or recommended phase 2 dose (RP2D), are usually inadequate and risky for novel oncology drugs.Due to the regulatory efforts aimed at improving dose optimisation in oncology drug development, clinical dose selection is now shifting away from these traditional methods towards a comprehensive benefit/risk assessment-based approach. Quantitative pharmacology analysis (QPA) plays a crucial role in this new paradigm. This mini-review summarises the use of QPA in selecting the starting dose for oncology FIH studies and potential efficacious doses for expansion or phase 2 trials. QPA allows for a more rational and scientifically based approach to dose selection by integrating information across studies and development phases.In conclusion, the application of QPA in oncology drug development has the potential to significantly enhance the success rates of clinical trials and ultimately support clinical decision-making, particularly in dose selection.

The novel myeloperoxidase inhibitor verdiperstat was developed as a treatment for neuroinflammatory and neurodegenerative diseases. During development, a computational prediction of verdiperstat liver safety was performed using DILIsym v8A, a quantitative systems toxicology (QST) model of liver safety.A physiologically-based pharmacokinetic (PBPK) model of verdiperstat was constructed in GastroPlus 9.8, and outputs for liver and plasma time courses of verdiperstat were input into DILIsym. In vitro experiments measured the likelihood that verdiperstat would inhibit mitochondrial function, inhibit bile acid transporters, and generate reactive oxygen species (ROS); these results were used as inputs into DILIsym, with two alternate sets of parameters used in order to fully explore the sensitivity of model predictions. Verdiperstat dosing protocols up to 600 mg BID were simulated for up to 48 weeks using a simulated population (SimPops) in DILIsym.Verdiperstat was predicted to be safe, with only very rare, mild liver enzyme increases as a potential possibility in highly sensitive individuals. Subsequent Phase 3 clinical trials found that ALT elevations in the verdiperstat treatment group were generally similar to those in the placebo group. This validates the DILIsym simulation results and demonstrates the power of QST modelling to predict the liver safety profile of novel therapeutics.