Toxicogenomics applied to predictive and exploratory toxicology for the safety assessment of new chemical entities: a long road with deep potholes

In vitro Toxico-genomics of Etoposide Loaded Gelatin Nanoparticles and Its in-vivo Therapeutic Potential: Pharmacokinetics, Biodistribution and Tumor Regression in Ehrlich Ascites Carcinoma (EAC) Mice Model

Globally, breast cancer is the foremost cause of mortality among women detected with cancer, with 21% diagnosed in India alone. Etoposide loaded gelatin nanoparticles (EGNP) were prepared and its physical characterization (size:150nm±0.241; zeta potential −29.32 mV) was done along with in-vitro studies to assess biotoxicity, intracellular ROS, cell cycle arrest and death caused by EGNPs. We report the molecular pathways induced by EGNP in-vitro, pharmacokinetics, biodistribution and tumor regression in-vivo in Balb/c mice.Gene expression profiling of Bax, Bcl2, p53, Caspase-3, RIPK1, RIPK3 and ß-actin as internal control were done by RT-PCR wherein Etoposide and EGNP treated MCF-7 cells showed higher expressions of apoptotic genes-Bax, p53, caspase-3, lower expression of anti-apoptotic gene-Bcl2 when compared to control. Enhanced expression of necroptosis-RIPK1 were observed, while RIPK3 was insignificant. Since, RIPK1 regulates necroptosis and apoptosis, expression of apoptotic markers confirmed apoptotic molecular mechanisms. Negligible hemolysis of Gelatin nanoparticles (GNP), and EGNP at selected dosages confirmed biocompatibility. In vivo pharmacokinetics and biodistribution were done by 99Tc-labelled nanoparticles indicating increased circulation of EGNPs, allowing accumulation at the tumor site by Enhanced permeability and retention (EPR) phenomena. Tumor regression indicates the efficacy of EGNP by reducing the tumor burden when compared to void GNP and Etop per se, resulting in increased life span. High biocompatibility and bio-efficacy of EGNPs prove their therapeutic potential in cancer treatment.

Identification of in vitro and in vivo disconnects using transcriptomic data

BACKGROUND

Integrating transcriptomic experiments within drug development is increasingly advocated for the early detection of toxicity. This is partly to reduce costs related to drug failures in the late, and expensive phases of clinical trials. Such an approach has proven useful both in the study of toxicology and carcinogenicity. However, general lack of translation of in vitro findings to in vivo systems remains one of the bottle necks in drug development. This paper proposes a method for identifying disconnected genes between in vitro and in vivo toxicogenomic rat experiments. The analytical framework is based on the joint modeling of dose-dependent in vitro and in vivo data using a fractional polynomial framework and biclustering algorithm.

RESULTS

Most disconnected genes identified belonged to known pathways, such as drug metabolism and oxidative stress due to reactive metabolites, bilirubin increase, glutathion depletion and phospholipidosis. We also identified compounds that were likely to induce disconnect in gene expression between in vitro and in vivo toxicogenomic rat experiments. These compounds include: sulindac and diclofenac (both linked to liver damage), naphtyl isothiocyanate (linked to hepatoxocity), indomethacin and naproxen (linked to gastrointestinal problem and damage of intestines).

CONCLUSION

The results confirmed that there are important discrepancies between in vitro and in vivo toxicogenomic experiments. However, the contribution of this paper is to provide a tool to identify genes that are disconnected between the two systems. Pathway analysis of disconnected genes may improve our understanding of uncertainties in the mechanism of actions of drug candidates in humans, especially concerning the early detection of toxicity.

Application of toxicogenomic tools in the drug research and development process

The cost for the development of new active and safe drugs is higher than ever and continues to increase. At the same time, both the pharmaceutical industry and the Regulatory Authorities are, despite the increasing effort to develop safer drugs, concerned by the risk of unexpected side effects observed in the late steps of the development of new drugs, either in late clinical development or after marketing approval. Then, the early knowledge of any potential toxic effect of a new drug is a key issue to allow adequate decision making. This means that current approaches based on the determination of the No-Adverse-Effect-Level and the Human-Equivalent-Dose are far from being perfect, and fail mainly to detect toxic phenomena of low intensity and/or low frequency. To improve the predictability of the existing experimental models, Toxicogenomics could be included into the in vitro candidate-selection steps and/or during the regulatory preclinical (or clinical) studies. In this communication, the authors present an example of the use of Toxicogenomic data to support decision making when selecting a new candidate to regulatory development. The authors also present a second example of integration of Toxicogenomics with the animal regulatory studies within the preclinical development of a new drug.