New Paradigm For Drug Development Research Articles

Artificial Intelligence and Anticancer Drug Development-Keep a Cool Head.

Artificial intelligence (AI) is progressively spreading through the world of health, particularly in the field of oncology. AI offers new, exciting perspectives in drug development as toxicity and efficacy can be predicted from computer-designed active molecular structures. AI-based in silico clinical trials are still at their inception in oncology but their wider use is eagerly awaited as they should markedly reduce durations and costs. Health authorities cannot neglect this new paradigm in drug development and should take the requisite measures to include AI as a new pillar in conducting clinical research in oncology.

Patient-centric Clinical Trials: A New Paradigm for Drug Development

With the acceleration of innovative drugs launched in the market, clinical trials have become increasingly complex and costly. Integration of patients' perspective and engagement into the clinical research process is essential to the success of the trials, which leads to the emergence of the concept of patient-centric clinical trials. Compared to the conventional paradigm of clinical trials, patient-centric clinical trials have the potential to increase the feasibility of study protocol, to speed recruitment and execution, and to promote the success of trials. It calls for the institutions and investigators of clinical trials to be aware of and adapt to patient-centric initiatives. In this article, we highlight technologies and actions that can be used to enhance patients' engagement in the entire process of drug development, covering protocol development, trial conduction, and result publication.

Abstract 255: Antagonizing Na-K-Cl cotransporter NKCC1 impairs medulloblastoma cell viability

Abstract Medulloblastoma, a common pediatric brain cancer, is comprised of four molecular subgroups: Wnt-activated; Shh-activated; group 3; and group 4. Group 3 subgroup patients have the lowest survival rate and the highest rates of relapse and metastasis [1]. The standard-of-care for medulloblastoma consists of surgical removal of the tumor, radiation, and chemotherapy [1]. However, the standard-of-care poses many risk factors including hearing loss, permanent damage to endocrine and neurocognitive function, and secondary tumors [1]. There is a high demand for new treatment options for medulloblastoma. Interestingly, group 3 medulloblastoma tumors have high expression of GABRA5 and SLC12A2, which code for the α5-subunit of the ligand-gated ionotropic γ-aminobutyric acid type A receptor (GABAAR) and the sodium-potassium-chloride cotransporter isoform-1 (NKCC-1), respectively [2]. Several recent studies have provided evidence that ion channel activity contributes to brain cancer progression [3]. If so, then modulating ion channel(s) function may impair cancer cell viability. We have already shown that use of a positive allosteric modulator of the GABAAR can impair viability of group 3 medulloblastoma cells in vitro and in vivo and with greater specificity and potency than standard-of-care chemotherapeutic [4, 5]. Others have shown that inhibition or down-regulation of NKCC-1 can reduce cell viability, increase apoptosis, and decrease migration and invasion of cells derived from various cancer types [3]. We have examined how modulating NKCC-1 and GABAAR alone and simultaneously impacts the viability of group 3 medulloblastoma cells. We find that there is a synergistic effect in the inhibition of NKCC-1 and positive modulation of GABAAR. We will report on these observations and our model for the mechanism of action.

Organs-on-a-chip

In the last few years, considerable attention has been given to in vitro models in an attempt to reduce the use of animals and to decrease the rate of preclinical failure associated with the development of new drugs. Simple two-dimensional cultures grown in a dish are now frequently replaced by organotypic cultures with three-dimensional (3-D) architecture, which enables interactions between cells, promoting their differentiation and increasing their in vivo likeness. Microengineering now enables the incorporation of small devices into 3-D culture models to reproduce the complex microenvironment of the modeled organ, often referred to as organs-on-a-chip (OoCs). This review describes various OoCs developed to mimic liver, brain, kidney, and lung tissues. Current challenges encountered in attempts to recreate the in vivo environment are described, as well as some examples of OoCs. Finally, attention is given to the ongoing evolution of OoCs with the aim of solving one of the major limitations in that they can only represent a single organ. Multi-organ-on-a-chip (MOC) systems mimic organ interactions observed in the human body and aim to provide the features of compound uptake, metabolism, and excretion, while simultaneously allowing for insights into biological effects. MOCs might therefore represent a new paradigm in drug development, providing a better understanding of dose responses and mechanisms of toxicity, enabling the detection of drug resistance and supporting the evaluation of pharmacokinetic–pharmacodynamics parameters.

First In Vivo Testing of Compounds Targeting Group 3 Medulloblastomas Using an Implantable Microdevice as a New Paradigm for Drug Development.

Medulloblastoma is the most common childhood malignant brain tumor. The most lethal medulloblastoma subtype exhibits a high expression of the GABAA receptor α5 subunit gene and MYC amplification. New benzodiazepines have been synthesized to function as α5-GABAA receptor ligands. To compare their efficacy with that of standard-of-care treatments, we have employed a newly developed microscale implantable device that allows for high-throughput localized intratumor drug delivery and efficacy testing. Microdoses of each drug were delivered into small distinct regions of tumors, as confirmed by tissue mass spectrometry, and the local drug effect was determined by immunohistochemistry. We have identified a benzodiazepine derivative, KRM-II-08, as a new potent inhibitor in several α5-GABAA receptor expressing tumor models. This is the first instance of in vivo testing of several benzodiazepine derivatives and standard chemotherapeutic drugs within the same tumor. Obtaining high-throughput drug efficacy data within a native tumor microenvironment as detailed herein, prior to pharmacological optimization for bioavailability or safety and without systemic exposure or toxicity, may allow for rapid prioritization of drug candidates for further pharmacological optimization.

The curious stories of drugs with two lives: a new paradigm in drug development.

The curious stories of drugs with two lives: a new paradigm in drug development.

Developing New Drug Treatments in the Era of Network Medicine

Although impressive advances have been made in determining the genetic and molecular causes of disease, treatment for many complex diseases remains inadequate. Despite compelling unmet medical needs and new insights into disease pathobiology, new drug approvals for complex diseases have stagnated. A new paradigm for drug development is needed, and key concepts from network medicine and systems pharmacology may be essential to this effort.

Identification and Characterization of Small Molecule Inhibitors of a Plant Homeodomain Finger

A number of histone-binding domains are implicated in cancer through improper binding of chromatin. In a clinically reported case of acute myeloid leukemia (AML), a genetic fusion protein between nucleoporin 98 and the third plant homeodomain (PHD) finger of JARID1A drives an oncogenic transcriptional program that is dependent on histone binding by the PHD finger. By exploiting the requirement for chromatin binding in oncogenesis, therapeutics targeting histone readers may represent a new paradigm in drug development. In this study, we developed a novel small molecule screening strategy that utilizes HaloTag technology to identify several small molecules that disrupt binding of the JARID1A PHD finger to histone peptides. Small molecule inhibitors were validated biochemically through affinity pull downs, fluorescence polarization, and histone reader specificity studies. One compound was modified through medicinal chemistry to improve its potency while retaining histone reader selectivity. Molecular modeling and site-directed mutagenesis of JARID1A PHD3 provided insights into the biochemical basis of competitive inhibition.

Stem Cells asIn VitroModel of Parkinson's Disease

Progress in understanding neurodegenerative cell biology in Parkinson's disease (PD) has been hampered by a lack of predictive and relevant cellular models. In addition, the lack of an adequate in vitro human neuron cell-based model has been an obstacle for the uncover of new drugs for treating PD. The ability to generate induced pluripotent stem cells (iPSCs) from PD patients and a refined capacity to differentiate these iPSCs into DA neurons, the relevant disease cell type, promises a new paradigm in drug development that positions human disease pathophysiology at the core of preclinical drug discovery. Disease models derived from iPSC that manifest cellular disease phenotypes have been established for several monogenic diseases, but iPSC can likewise be used for phenotype-based drug screens in complex diseases for which the underlying genetic mechanism is unknown. Here, we highlight recent advances as well as limitations in the use of iPSC technology for modelling PD “in a dish” and for testing compounds against human disease phenotypes in vitro. We discuss how iPSCs are being exploited to illuminate disease pathophysiology, identify novel drug targets, and enhance the probability of clinical success of new drugs.

Induced pluripotent stem cells — opportunities for disease modelling and drug discovery

The ability to generate induced pluripotent stem cells (iPSCs) from patients, and an increasingly refined capacity to differentiate these iPSCs into disease-relevant cell types, promises a new paradigm in drug development - one that positions human disease pathophysiology at the core of preclinical drug discovery. Disease models derived from iPSCs that manifest cellular disease phenotypes have been established for several monogenic diseases, but iPSCs can likewise be used for phenotype-based drug screens in complex diseases for which the underlying genetic mechanism is unknown. Here, we highlight recent advances as well as limitations in the use of iPSC technology for modelling a 'disease in a dish' and for testing compounds against human disease phenotypes in vitro. We discuss how iPSCs are being exploited to illuminate disease pathophysiology, identify novel drug targets and enhance the probability of clinical success of new drugs.

Adaptive clinical trials in oncology

Modern oncology drug development faces challenges very different from those of the past and it must adapt accordingly. The size and expense of phase III clinical trials continue to increase, but the success rate remains unacceptably low. Adaptive trial designs can make development more informative, addressing whether a drug is safe and effective while showing how it should be delivered and to whom. An adaptive design is one in which the accumulating data are used to modify the trial's course. Adaptive designs are ideal for addressing many questions at once. For example, a single trial might identify the appropriate patient population, dose and regimen, and therapeutic combinations, and then switch seamlessly into a phase III confirmatory trial. Adaptive designs rely on information, including from patients who have not achieved the trial's primary end point. Longitudinal models of biomarkers (including tumor burden assessed via imaging) enable predictions of primary end points. Taking a Bayesian perspective facilitates building an efficient and accurate trial, including using longitudinal information. A wholly new paradigm for drug development exemplifying personalized medicine is evinced by an adaptive trial called I-SPY2, in which drugs from many companies are evaluated in the same trial--a phase II screening process.

Progress towards personalized medicine

Personalized medicine is the tailoring of therapies to defined subsets of patients based on their likelihood to respond to therapy or their risk of adverse events. The advent of improved genomic tools has greatly hastened our understanding of the molecular pathology of diseases, enabling us to redefine disease at the molecular level. The development of molecularly targeted therapies, coupled with improved diagnostic criteria, holds the promise of delivering a new paradigm in drug development. But how far have we come, and how close is personalized medicine to delivering on its promise?

Expression profiling of drug response - from genes to pathways

Understanding individual response to a drug-what determines its efficacy and tolerability-is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P-450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient. However, experiments are "noisy" and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of high-throughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research-the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient.

Toxicogenomics in drug development.

Toxicogenomics represents the merging of toxicology with technologies that have been developed, together with bioinformatics, to identify and quantify global gene expression changes. It represents a new paradigm in drug development and risk assessment, which promises to generate a wealth of information towards an increased understanding of the molecular mechanisms that lead to drug toxicity and efficacy, and of DNA polymorphisms responsible for individual susceptibility to toxicity. Gene expression profiling, through the use of DNA microarray and proteomic technologies will aid in establishing links between expression profiles, mode of action and traditional toxic endpoints. Such patterns of gene expression, or 'molecular fingerprints' could be used as diagnostic or predictive markers of exposure, that is characteristic of a specific mechanism of induction of that toxic or efficacious effect. It is anticipated that toxicogenomics will be increasingly integrated into all phases of the drug development process particularly in mechanistic and predictive toxicology, and biomarker discovery. This review provides an overview of the expression profiling technologies applied in toxicogenomics. and discusses the promises as well as the future challenges of applying this discipline to the drug development process.