Bayesian Statistics in Drug Development
Harry Yang, Steven J. Novick in Bayesian Analysis with R for Drug Development, 2019
Understanding the causes of a disease often leads to the identification of a biological target. A biological target is any component in a living organism that influences the disease. Examples of common biological targets include genes and proteins. As previously noted (PhRMA 2015), even at this early stage of drug discovery, it is critical to choose a target that can potentially interact with and be affected by a drug molecule. After a target is identified, its association with the disease must be validated through in vitro and in vivo experiments. Drawing from the understanding of underpinnings of the disease and the potential target, scientists begin to find a drug molecule that can interact with the target and change the course of the disease. Most notable among various methods used for this purpose are 1) screening chemical libraries of synthetic small molecules, natural products, or extracts using in vitro assays (usually low-to-medium throughput) to look for compounds of desired therapeutic effect (https://en.wikipedia.org/wiki/Drug_discovery); 2) high-throughput screening of large compound libraries in search of disease-altering molecules; and 3) genetically engineering of molecules that have high affinity to the target. These lead compounds advance to the next stage of testing in which their toxic-kinetic properties are evaluated in cell and animal models. Those compounds that meet the selection criteria are further optimized to increase affinity, selectivity, efficacy, and stability.
Static Magnetic Therapy for Pain
Mark V. Boswell, B. Eliot Cole in Weiner's Pain Management, 2005
Most, if not all, commercially available permanent therapeutic magnets generate much stronger magnetic fields at their surfaces than the geomagnetic field. Strong magnetic fields may not be enough to produce useful biological effects, however. The geometry of the field in relation to the biological target may be important. Or, temporal and spatial variation in the field may be as, or more, important than field strength. This means that it is important to know what characteristic(s), or metric, of magnetic fields can be sensed. The process by which an externally applied magnetic field leads to a biological result can be conceived to involve a series of elements, perhaps something like the cascade in Figure 84.1. First, there must be a sensor(s) to detect the field. Next, a transduction mechanism(s) must couple detection to an effector system or systems. This produces biological effects. In the present context, the concept of “magnetotherapy” demands that an applied magnetic field can in some way interact with the nociceptive process to relieve “pain.” Clinicians and scientists are trained to observe the behavioral and therapeutic effects of the intervention. Herein lies a conceptual framework for studying magnetic fields from bench to bedside. This is not unlikely the process of developing pharmaceutical agents, but many details about magnetic fields remain to be discovered.
Key Concepts in Assay Development, Screening and the Properties of Lead and Candidate Compounds
Venkatesan Jayaprakash, Daniele Castagnolo, Yusuf Özkay in Medicinal Chemistry of Neglected and Tropical Diseases, 2019
It is important to ensure that a common set of definitions is used in the drug discovery value chain so that all stakeholders have a common basis for expectations when evaluating compounds. Commonly accepted definitions in the pre-clinical stages are: Biological Target: A macromolecule with known function, disease association and involvement, and ideally 3-dimensional structure.Validated Hit: A molecule with robust dose-response activity in an assay that utilises the target protein with confirmed structure and preliminary SAR information.Lead Compound: A representative compound series which satisfies predefined criteria (see Table 1) for progression to Lead-to-Candidate optimisation.Candidate: A representative compound that satisfies predefined criteria (see Table 2) for progression to subsequent IND submission.
Entering the era of computationally driven drug development
Published in Drug Metabolism Reviews, 2020
Neha Maharao, Victor Antontsev, Matthew Wright, Jyotika Varshney
The PK component provides the time course of measured drug concentrations usually in plasma (Cp) and PK models can be used to model the disposition kinetics. A suitable mathematical function describes the relationship between drug concentration in plasma and the tissue of interest (Ce, biophase concentration) (Jusko et al. 1995; Wright et al. 2011). The biophase drug levels are believed to be the driving force for the pharmacological effects (Mager et al. 2003). Drug molecules at the site of action interact with the biological target, usually a receptor or an enzyme. The biophase sensor process encompasses the kinetics of reversible or irreversible binding and dissociation of drug–receptor or drug–enzyme complexes (Jusko et al. 1995; Wright et al. 2011). These drug–biological target interactions may directly or indirectly increase or reduce the production (kin) or dissipation (kout) of endogenous substances, which may represent the desired PD effect (Jusko et al. 1995; Mager et al. 2003). Often, however, the altered levels of endogenous substrates trigger a further dynamic transduction process ultimately leading to an acute or long-lasting pharmacological effect (E) (Mager et al. 2003). PK/PD modeling enables mathematical characterization of the relationship between PK and PD and hence is applied to all stages of drug development.
The latest automated docking technologies for novel drug discovery
Published in Expert Opinion on Drug Discovery, 2021
Julio Caballero
The design of a drug that specifically binds to a relevant biological target is the common task of medicinal chemists. However, the development of multitarget drugs for the treatment of diseases is a more efficient way to reduce drug resistance and toxicity. Multitarget drug design is an endeavor that uses experimentally validated structural protein-ligand information in PDB, and computational methods, such as shape screening, pharmacophore screening, and reverse (or inverse) molecular docking [37,38], where the binding of an active compound is explored against multiple clinically relevant target proteins (Figure 1). In this sense, a reverse docking protocol can be employed to identify novel protein targets for a drug. As a result, a novel mechanism of action or side effect for the drug can be proposed. Reverse docking can be also used to discover innovative treatments using abandoned and existing molecules/drugs (drug repositioning and drug rescue approaches) [39].
A multiparametric organ toxicity predictor for drug discovery
Published in Toxicology Mechanisms and Methods, 2020
Chirag N. Patel, Sivakumar Prasanth Kumar, Rakesh M. Rawal, Daxesh P. Patel, Frank J. Gonzalez, Himanshu A. Pandya
The drug discovery process was initiated in the year 1806 when a hypnotic agent called morphine was synthesized. However, the first attempt of drug discovery was mostly attributed to the Avogadro’s atomic hypothesis and coal-tar derivatives synthesis in the 1870s. The process of drug discovery starts with the identification of biological target and lead discovery (candidate, synthesis, characterization, high-throughput screening and assays for therapeutic efficacy) followed by lead optimization through pharmacokinetics and pharmacodynamics studies with preclinical and clinical development (phase-1, 2, 3 and 4). The newly synthesized drug should be approved by United States Food and Drug Administration (USFDA) before introducing to the market. This whole process takes around 15–20 years with massive financial investment. The rational drug design includes new drug discovery based on the knowledge of biological target pertain to therapeutic benefit. However, it mainly focuses on the accurate calculations of binding affinity calculations through customized structure-based approaches.