Mechanisms of drug toxicity and relevance to pharmaceutical development

Abstract

Toxicity has been estimated to be responsible for the attrition of approximately one-third of drug candidates and is a major contributor to the high cost of drug development, particularly when not recognized until late in clinical trials or post-marketing. The causes of drug toxicity can be classified in several ways and include mechanism-based (on-target) toxicity, immune hypersensitivity, off-target toxicity, and bioactivation/covalent modification. In addition, idiosyncratic responses are rare but can be one of the most problematic issues; several hypotheses for these have been advanced. Although covalent binding of drugs to proteins was described almost 40 years ago, the significance to toxicity has been difficult to establish; recent literature in this field is considered. The development of more useful biomarkers and short-term assays for rapid screening of drug toxicity early in the drug discovery/development process is a major goal, and some progress has been made using "omics" approaches.

Fig. 1

Estimates of fractions of reasons for attrition of drug candidates in pre-clinical and clinical development (ca. 2000).²⁾

Fig. 2

Safety issues at different stages of drug discovery and development.¹⁾

Fig. 3

Hypothetical relationship between the inherent toxicity of drugs and the variability of the response among hosts (e.g. test animals, humans). The dose is not a consideration in this treatment, adapted from Zimmerman.^9,10) At toxic doses, the most readily understood compounds are those with high toxicity in all animal species. Variation among species introduces more uncertainty in extrapolation to humans. Predictions can be made if the issue is metabolism but idiosyncratic problems are very difficult to understand with animal models.

Fig. 4

A general scheme of biological events related to the toxicity of drugs and other chemicals.^4,28)

Fig. 5

Relationship between in vitro covalent binding (rate of reactive metabolites to microsomal proteins (10 µM substrate) and in vivo covalent binding (rate) in rat liver tissue after administration of labeled compounds (at 20 mg/kg). Three different models were used.⁵⁷⁾ 1, Furosemide; 2, tienilic acid; 3, clozapine, 4, imipramine; 6, acetaminophen; 6, indomethacin; 7, carbamazepine; 8, diclofenac.

Fig. 6

Comparisons of hepatoxins (▲) and non-hepatoxins (■) for estimates of total daily dose of covalently bound material extrapolated from in vitro liver microsomal covalent binding and doses. APAP, acetaminiophen; BEN, benoxaprofen; BUS, buspirone; CAR, carbamazepine; DIC, diclofenac; DIPH, diphenhydramine; FEC, felbamate; IBU, ibuprofen; IND, indomethacin; MEL, meloxicam; NEF, nefazodone; PAR, paroxetine; PRO, propranolol; RAL, raloxifene; SIM, simvastatin; SUD, sudoxicam; TA, tienilic acid; THEO, theophylline.⁵⁸⁾

Fig. 7

Categorization of hepatoxins and nonhepatotoxins based on estimated total daily body burden covalent binding from human hepatocyte data.⁵⁹⁾ See Figure 6 for drug abbreviations.

Fig. 8

Scatter plots of (A) percentage GSH adduct formation and (B) estimated total daily covalent adduct burden in “drug-induced toxicity” (DIT, Δ) and non-drug-induced toxicity (Non-DIT, O) groups of chemicals.⁶⁰⁾ Horizontal lines are drawn at a (A) 0.2% adduct level and (B) 1 mg body level.

Fig. 9

(A) Traditional in vitro or in vivo toxicity program. (B) Idealized in vitro toxicogenomics system.

Fig. 10

An in vivo predictive toxicogenomics paradigm for database development. The model shown here is the DrugMatrix^® system developed by Iconix (now part of Entelos).²⁸⁾

Fig. 11

Uses of toxicity data at various stages of drug discovery and development. Major steps in the process are shown in boxes, with relevant screens listed below.²⁸⁾