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Nonclinical Safety Evaluation of Drugs
Published in Pritam S. Sahota, James A. Popp, Jerry F. Hardisty, Chirukandath Gopinath, Page R. Bouchard, Toxicologic Pathology, 2018
Thomas M. Monticello, Jeanine L. Bussiere
In vitro screening to identify other possible safety liabilities, such as “off-target” (secondary) pharmacology, is a growing and evolving field that is becoming more standard during lead optimization (Bowes et al. 2012; Papoian et al. 2015; Whitebread et al. 2016). In vitro profiling involves the screening of compounds against a broad range of targets that can include receptors, ion channels, enzymes, and transporters. These targets are often distinct from the intended pharmacologic target and may be the cause of unexpected toxicities observed either in the animal study or in the clinic. Various protocols are commonly available and, in general, consist of binding assays, functional assays, and enzyme assays that can provide important information on the pharmacological activity of a drug candidate in addition to possible unanticipated side effects. Current regulatory guidance does not indicate which targets of interest need to be screened via in vitro pharmacology profiling. However, when the data suggest possible off-target activity, the extent of that risk, under clinical conditions and drug exposures, need to be carefully assessed.
Identification and Use of Biomarkers in Preclinical Toxicologic Safety Assessment
Published in Anthony P. DeCaprio, Toxicologic Biomarkers, 2006
Donna M. Dambach, Jean-Charles Gautier
Fundamental to the process of target proof-of-concept is the use of in vitro models and animal models. These approaches are utilized in a similar manner as surrogate models for the assessment of potential off-target or chemical-based toxicity, and the same criteria are also applied to these toxicity models, i.e., the molecular target of interest is expressed and/or the model system has some relevance to in vivo application (8). With respect to both pharmacology-based and chemical-based toxicity, a major concern is off-target activity due to binding of related molecular targets or due to a compound substructure interacting with nontarget sites. An additional area of concern is toxicity related to the metabolic fate of a compound. As such, a significant aspect of risk assessment during the preclinical discovery period is oriented toward these types of assessment. Many surrogate biomarker platforms already exist in later development to assess these issues, e.g., genotoxicity assays and in-life safety assessments; however, these assessments are now often initiated during the discovery period through the use of additional biomarker platforms that take advantage of in vitro systems and the application of molecular-based technologies. The goals of these earlier assays are to: (i) serve as higher throughput screens to “flag” potential liabilities or as predictors of an outcome, i.e., those that have good concordance or high sensitivity and specificity, and (ii) have minimal compound requirements.
Latest generation estrogen receptor degraders for the treatment of hormone receptor-positive breast cancer
Published in Expert Opinion on Investigational Drugs, 2022
Ya-Chi Chen, Jiajie Yu, Ciara Metcalfe, Tom De Bruyn, Thomas Gelzleichter, Vikram Malhi, Pablo D. Perez-Moreno, Xiaojing Wang
Amcenestrant has demonstrated potent antagonist and degradative properties against ER both in vitro and in vivo and binds with high affinity to human wild-type or mutant ERα (ERα-Y537S and ERα-D538G) [65,66]. Amcenestrant antagonizes mutant ERα with lower potency than wild-type ERα (EC50 = 20 nM [wild type], 331 nM [ERα-Y537S mutant], 595 nM [ERα-D538G mutant]) [66]. Across a large panel of ER-positive cells, amcenestrant demonstrated broad and superior ER degradation activity as compared with SERD/SERM hybrids (i.e. GDC-0810 and AZD9496) including improved inhibition of ER signaling and inhibition of cell growth [66]. Amcenestrant effectively induces ERα degradation in MCF-7 cells at subnanomolar concentrations (DC50 of 0.2 nmol/L) with maximal degradation levels of 98% comparable to the in vitro activity of fulvestrant [65,66]. In a tamoxifen-sensitive MCF-7 xenograft tumor model, amcenestrant exhibited dose-dependent tumor-growth inhibition and tumor regression was achieved with a 25 mg/kg twice daily (bid) oral dose [65,66]. In the HCI-013 PDX model, significant tumor regressions were achieved at oral doses of amcenestrant 12.5 and 25 mg/kg bid [66]. Amcenestrant did not have any agonist effect in rat uterine assays at doses of 25, 50, or 100 mg/kg daily [66]. No off-target activity (IC50 ≤ 1 μM) was detected during in vitro selectivity assays [65].
Melflufen for the treatment of multiple myeloma
Published in Expert Review of Clinical Pharmacology, 2022
Enrique M. Ocio, Omar Nadeem, Fredrik Schjesvold, Francesca Gay, Cyrille Touzeau, Meletios A. Dimopoulos, Paul G. Richardson, Maria-Victoria Mateos
Recently, a chimeric antigen receptor T-cell therapy, idecabtagene vicleucel (ide-cel; bb2121) was approved by the US Food and Drug Administration (FDA) for patients with MM after at least four prior lines of therapy, including an IMiD, PI, and anti-CD38 mAb [12]. Classes of drugs in late-stage development that might provide new treatment options for these patients include bispecific antibodies/T-cell engagers (e.g. CC93269, teclistamab) [13,14], antibody-drug conjugates (e.g. belantamab mafodotin [GSK2857916]) [15], anti-Bcl-2 agents (e.g. venetoclax) [16], cereblon E3 ligase modulators (CELMoDs; e.g. iberdomide, CC-92480) [17,18], and selective inhibitors of nuclear export (e.g. selinexor) [19]. Each of these represents a targeted approach to therapy that seeks to minimize off-target activity (likely to cause toxicity), while maximizing on-target effects (likely to increase efficacy), for a more favorable therapeutic ratio. Two of these first-in-class agents recently received FDA approval: selinexor, which, in combination with dexamethasone, provided a 26% overall response rate (ORR) in patients with triple-class-refractory MM in the STORM study [20], and belantamab mafodotin, which was associated with a 31−34% ORR in DREAMM-2 [21,22]. A third first-in-class targeted cytotoxic agent recently approved by the US FDA for an MM indication is the subject of this review.
Artificial intelligence, machine learning, and drug repurposing in cancer
Published in Expert Opinion on Drug Discovery, 2021
Ziaurrehman Tanoli, Markus Vähä-Koskela, Tero Aittokallio
Molecular docking is a widely used in-silico method in structure-based drug design, due to its ability to predict the binding-conformation of small molecule ligands to the appropriate target-binding site [95–97]. The drawback of molecular docking is that the 3D structures of many target proteins have not yet been resolved, which is required for running the docking simulations. Furthermore, the accuracy of docking-based methods decreases in cases where the number of known ligands for a protein is not sufficient [98]. Regardless of these limitations, there are several examples of successful docking-based drug off-target activity predictions [99]. For instance, antipsychotic agent thioridazine was found among 1500 FDA-approved compounds to possess anti-inflammatory activity by binding and inhibiting IκB kinase, which is critical for the NF-ΚB pathway [100]. Similarly, virtual docking accurately predicted inhibitory activity of five compounds from a collection of more than 1400 FDA-approved drugs against Pseudomonas aeruginosa quorum-sensing (population-wide virulence) mechanisms, with antipsychotic agent pimozide displaying potent in vitro activity in inhibiting bacterial virulence gene expression [101]. Moreover, AI is also emerging as an increasingly accurate approach for predicting the 3D structures of proteins from their amino-acid sequences [102,103].