Biotherapeutics: Challenges and Opportunities for Predictive Toxicology of Monoclonal Antibodies.

Biotherapeutics are a rapidly growing portion of the total pharmaceutical market accounting for almost one-half of recent new drug approvals. A major portion of these approvals each year are monoclonal antibodies (mAbs). During development, non-clinical pharmacology and toxicology testing of mAbs differs from that done with chemical entities since these biotherapeutics are derived from a biological source and therefore the animal models must share the same epitopes (targets) as humans to elicit a pharmacological response. Mechanisms of toxicity of mAbs are both pharmacological and non-pharmacological in nature; however, standard in silico predictive toxicological methods used in research and development of chemical entities currently do not apply to these biotherapeutics. Challenges and potential opportunities exist for new methodologies to provide a more predictive program to assess and monitor potential adverse drug reactions of mAbs for specific patients before and during clinical trials and after market approval.

Human recombinant arginase enzyme reduces plasma arginine in mouse models of arginase deficiency.

Arginase deficiency is caused by deficiency of arginase 1 (ARG1), a urea cycle enzyme that converts arginine to ornithine. Clinical features of arginase deficiency include elevated plasma arginine levels, spastic diplegia, intellectual disability, seizures and growth deficiency. Unlike other urea cycle disorders, recurrent hyperammonemia is typically less severe in this disorder. Normalization of plasma arginine levels is the consensus treatment goal, because elevations of arginine and its metabolites are suspected to contribute to the neurologic features. Using data from patients enrolled in a natural history study conducted by the Urea Cycle Disorders Consortium, we found that 97% of plasma arginine levels in subjects with arginase deficiency were above the normal range despite conventional treatment. Recently, arginine-degrading enzymes have been used to deplete arginine as a therapeutic strategy in cancer. We tested whether one of these enzymes, a pegylated human recombinant arginase 1 (AEB1102), reduces plasma arginine in murine models of arginase deficiency. In neonatal and adult mice with arginase deficiency, AEB1102 reduced the plasma arginine after single and repeated doses. However, survival did not improve likely, because this pegylated enzyme does not enter hepatocytes and does not improve hyperammonemia that accounts for lethality. Although murine models required dosing every 48 h, studies in cynomolgus monkeys indicate that less frequent dosing may be possible in patients. Given that elevated plasma arginine rather than hyperammonemia is the major treatment challenge, we propose that AEB1102 may have therapeutic potential as an arginine-reducing agent in patients with arginase deficiency.

Evidence for a potential protective effect of carnitine-pantothenic acid co-treatment on valproic acid-induced hepatotoxicity.

Valproic acid is approved for treatment of seizures and manic episodes of bipolar disorder, and continues to be one of the most commonly prescribed antiepileptic drugs in the world. Hepatotoxicity is a rare but serious side effect resulting from its use, particularly in young patients. This adverse effect does not display normal dose-response curves and can be lethal in children. A review of the purported mechanisms of action suggest hepatotoxicity results from increased oxidative stress, caused by a reduction in beta-oxidation and an increase in activation of certain metabolizing enzymes. There is also evidence that both carnitine and pantothenic acid are involved in the regulation of valproic acid-induced hepatotoxic processes, and clinical evidence has shown that treatment with either compound shows protective effects against hepatotoxicity. These results suggest a potential increase in protective effects with cotreatment of carnitine and pantothenic acid.

Fusion of nonclinical and clinical data to predict human drug safety.

Adverse drug reactions continue to be a major cause of morbidity in both patients receiving therapeutics and in drug R&D programs. Predicting and possibly eliminating these adverse events remains a high priority in industry, government agencies and healthcare systems. With small molecule candidates, the fusion of nonclinical and clinical data is essential in establishing an overall system that creates a true translational science approach. Several new advances are taking place that attempt to create a 'patient context' mechanism early in drug research and development and ultimately into the marketplace. This 'life-cycle' approach has as its core the development of human-oriented, nonclinical end points and the incorporation of clinical knowledge at the drug design stage. The next 5 years should witness an explosion of what the author views as druggable and safe chemical space, pharmacosafety molecular targets and the most important aspect, an understanding of unique susceptibilities in patients developing adverse drug reactions. Our current knowledge of clinical safety relies completely on pharmacovigilance data from approved and marketed drugs, with a few exceptions of drugs failing in clinical trials. Massive data repositories now and soon to be available via cloud computing should stimulate a major effort in expanding our view of clinical drug safety and its incorporation into early drug research and development.

Biomarkers.

Biomarkers are characteristics objectively measured and evaluated as indicators of: normal biologic processes, pathogenic processes, or pharmacologic response(s) to a therapeutic intervention. In environmental research and risk assessment, biomarkers are frequently referred to as indicators of human or environmental hazards. Discovering and implementing new biomarkers for toxicity caused by exposure to a chemical either from a therapeutic intervention or accidentally through the environment continues to be pursued through the use of animal models to predict potential human effects, from human studies (clinical or epidemiologic) or biobanked human samples, or the combination of all such approaches. The key to discovering or inferring biomarkers through computational means involves the identification or prediction of the molecular target(s) of the chemical(s) and the association of these targets with perturbed biological pathways. Two examples are given in this chapter: (1) inferring potential human biomarkers from animal toxicogenomics data, and (2) the identification of protein targets through computational means and associating these in one example with potential drug interactions and in another case with increasing the risk of developing certain human diseases.

Functional consequences of mTOR inhibition.

TOR (target of rapamycin) is a serine-threonine protein kinase that is conserved across a diverse range of species from fungi to mammals. The signaling pathway that is anchored by TOR is also conserved across species. In mammals, mTOR integrates growth factor, amino acid, nutrient and energy sensing signals, and thus plays a major role in cell growth and proliferation, protein synthesis and autophagy. As a result of the pivotal role of mTOR in signaling, the aberrant regulation of mTOR has been implicated in several disease processes, including cancer, diabetes, ocular diseases and neurodegenerative disorders, as well as in lifespan extension. More recently, rapamycin (sirolimus) analogs that antagonize the mTOR signaling pathway have been approved for the treatment of several cancers. This review describes some recent advances in the understanding of mTOR signaling, with an emphasis on the functional consequences of mTOR inhibition and therapeutic intervention strategies.

Interactions between traditional Chinese medicines and Western therapeutics.

Traditional Chinese medicine (TCM) is a holistic approach to health that attempts to bring the body, mind and spirit into harmony. TCM is an essential part of the healthcare system in several Asian countries, and is considered a complementary or alternative medical system in most Western countries. An integration of the traditional Chinese and Western systems of medicine has begun in multiple medical centers internationally, and there is increasing evidence that several herbs and combinations of herbs used in TCM impart important pharmacological effects. The number of databases and compilations of herbs, herbal formulations, phytochemical constituents and molecular targets is increasing, primarily because of the widespread use of TCM in combination with Western drugs. The continued popularity of herbal remedies worldwide suggests that evidence-based research in this field, as well as information regarding the potential efficacy and safety of phytochemical constituents in herbs and TCM formulations, are essential, particularly when TCM is used in combination with other drugs. Herb-drug interactions are similar to drug-drug interactions in terms of their effects on ADME properties. Improvements in the knowledge of the molecular targets and metabolic pathways, as well as of the synergistic and inhibitory effects associated with important phytochemicals from herbs and herbal formulations, will lead to the development of rational approaches for the safe combination of healthcare systems from different cultures.

Biotherapeutic first-in-human dose selection: making use of preclinical markers.

First-in-human dose-selection criteria for biotherapeutics are changing, primarily based on severe adverse events in a single monoclonal antibody trial in healthy volunteers. Spurred by new EMA guidance, the minimum anticipated biological-effect level (MABEL) for estimating a starting human dose from exposure-response preclinical data have been introduced and should help to create long overdue target mechanism-based models focused on exposure-response relationships. Even though clarity of its application is still developing, this has the potential to become the model for most biotherapeutics in the future. However, maximizing benefit from MABEL will require increased efforts to define and create assays for relevant biomarkers of biological activity and safety as pharmacodynamic end points. Currently, this has not been realized sufficiently to make the model applicable to a majority of biotherapeutics; however, this review suggests how it can be applied universally with monoclonal antibodies.

Current HIV therapeutics: mechanistic and chemical determinants of toxicity.

This review discusses current recommendations for initial therapy in HIV-infected individuals and the toxicity of certain components of these therapeutic regimens. In developed regions, therapy is headed in a direction of individualized treatment where AIDS can be converted into a treatable, chronic disease that is characterized by viral loads below assay detection levels. In developing nations, where sophisticated diagnostics are less applicable, treatment continues on a population basis. Because nucleoside reverse transcriptase inhibitors remain a cornerstone of current recommended regimens both in developed and developing regions, the mechanistic and chemical determinants of mitochondrial toxicity are highlighted and discussed in detail.

Clustering and its application in multi-target prediction.

Drug discovery teams are beginning to apply non-screening techniques to make early associations between chemical structure and various biological and druggability characteristics of compound series. The increasing availability of multiple data sets and models of target potency, ADME characteristics, and toxicity allows a researcher from any discipline to draw quick associations with multiple endpoints on sets of compounds or chemical scaffolds. Cluster analysis, for instance, can be used to correlate screening potency with data predicted from both freely available and commercially available models. In the future researchers will be able to draw chemical-biological associations 'on-the-fly' using various clustering or similarity techniques to determine whether the proposed toxicity of a drug is related to its chemical structure or its proposed efficacy mechanism. In this review associations are illustrated with target potency data gleaned from the literature associated with CYP450 substrate predictions from GeneGo's MetaDrug.

Computational toxicology: heading toward more relevance in drug discovery and development.

Computational tools for predicting toxicity have been envisioned to have the potential to broadly impact the attrition rate of compounds in early research and development, and prove successful in predicting adverse drug reactions (ADRs) in patients enrolled in clinical trials, and particularly prior to the marketing of drugs. The impact of such tools to date, however, has been modest and relatively narrow in scope. It is important to note that advances within medical science and newer approaches in clinical development will require predictive toxicology applications to be viable, and therefore efforts must be directed into making these tools relevant to the goal of preventing undesired toxicity in patients. In this Editorial Opinion, the current status of computational toxicology within industry is reviewed and areas in which advances can be made are highlighted. While predicting the potential of a compound to induce specific ADRs continues to be a formidable task, the field of computational biology is now heading in a direction more relevant to human disease and adverse outcomes.

Web resources for drug toxicity.

Information on drug toxicity is used primarily by three segments of the health care industry: the consumer or patient, healthcare practitioners, and research and development (R&D) scientists in the pharmaceutical industry. The major focus of both consumers and health care practitioners is the provision of suitable information for the safe use of drugs for both individuals and specific patient populations. Therefore, accurate information on potential side effects and drug-drug and food-drug interactions is critical. For pharmaceutical scientists, the use of toxicity information is more complex and has become an essential part of the R&D process. The high rate of failures in drug development has precipitated the utilization of all available resources to gather relevant information that may improve the process of drug development. The web is a growing source of information and services for the pharmaceutical industry. Web-based resources for non-clinical drug development include tools for virtual discovery such as silico ADME/Toxicity programs, access to information regarding in vitro and in vivo testing, new data management options, and the latest regulatory guidelines and industry news. These resources are reviewed from the perspective of a toxicologist.