As discussed above, ADMET studies have historically focused on in vivo assays. These are, however, time- and resource-intensive, and are generally low throughput, which caused them to be put off until later in the development process, when more resources are released to study the few molecules that have advanced to this advanced stage. With the advent of in vitro high-throughput screening, molecular biology and miniaturization technologies in the 1990s, early ADMET assays were developed to predict in vivo animal and human results, at a level of cost-effectiveness appropriate for the discovery stage. This produced a major advance in the science of ADMET, and has created a new norm that drug-discovery programs follow in advancing compounds from hit to lead, from lead to advanced lead, and on to nominated clinical candidates. Now, early in the discovery phase, using human enzymes and human-origin cells, drug-discovery programs are able to obtain highly actionable information about the drug-likeness of their new molecules, their potential to reach target organs, and early indications of known human mechanisms of toxicities. ADMET assessment of varying complexity is now routinely done on compounds that have shown in vitro efficacy and at the same time with or just prior to demonstrating early proof of principle in vivo.
The application of early ADMET is unique to each drug-discovery program. The road from discovery to IND is not a straight line. It depends on the therapeutic area, route of administration, chemical series, and other parameters. Correspondingly, the importance of the various ADMET assays depends on the specifics of the drug-discovery program. ADMET assays can also be divided into those that are routine and those reserved for more advanced profiling, with the division being a function of cost effectiveness and the need for the specific information. For instance, one does not normally need to know during the hit-to-lead phase which transporters in the gastrointestinal tract or the brain are involved in transporting the drug; however, later in the development process this issue becomes more relevant.
In some cases the FDA has moved to require some of the new in vitro
ADMET assays. For example, in vitro
drug-drug interaction studies may now be conducted under the guidance from the FDA dated September 2006. The guidance document defines precisely how to conduct cytochrome P450 (CYP450) inhibition and induction and P-gp interaction studies [28
How should a discovery team employ early ADMET? The answer is not simple and formulaic: it is a process. It is useful to start from the ultimate goal and work backwards towards discovery. The drug discovery and development team should first define the target product profile, which includes indication, intended patient population, route of administration, acceptable toxicities, and ultimately will define the drug label. Of course, the target product profile invariably will evolve during the life of the project, but having its major parameters established at the start helps the team to keep their eyes on the ball and work in close collaboration between disciplines such as biology and chemistry, discovery and development, pre-clinical and clinical groups. Once the target product profile is identified, then major design elements of the phase II and III clinical trials can be outlined, which in turn lead to questions about the product's tolerable toxicity and safety, which will then define the regulatory toxicity and safety studies in animals, which will lead the team to the discovery and preclinical-development questions to be addressed via their specific early ADMET program.
In the discovery phase, at the beginning of this exciting and risky journey, how does one put this information into action? For example, if a compound has high target receptor binding and biological activity in cells and in relevant in vivo animal models, how can one maximize the chances of it becoming a successful drug some day? A molecule needs to cross many barriers on the way to its target. The first barrier is seemingly simple: solubility. A solubility screen will provide information about the NCE's solubility in fluids compatible with administration to humans. The next barrier is chemical and metabolic stability. Chemical stability in buffers, simulated gastric and intestinal fluids, and metabolic stability in plasma, hepatocytes or liver microsomes of different species can be measured to predict a compound's stability in the different environments it will encounter in the human body on the way to its target.
The second step is to define some of the absorption properties of the compounds. Are they likely to be bioavailable? Measurement of permeability across Caco-2 cell monolayers is a good predictor of human oral bioavailability. For CNS drugs, assessment of BBB penetration would come at this stage and is usually a part of lead optimization campaigns. Passive BBB permeability may be assessed using BBB-parallel artificial membrane permeability assays (BBB-PAMPAs), whereas potential for active uptake or efflux may be determined using in vivo models or relevant in vitro BBB models expressing efflux and influx transporters.
Measurement of binding to plasma proteins indicates the degree of availability of the free compound in the blood circulation. This is critical as only unbound drugs are able to get to the target and exert their pharmacological effects. Metabolism and drug-drug interaction issues can be detected by screening for inhibition of CYP-450 liver enzymes. All these assays allow chemists and biologists to obtain actionable information early, allowing them to gain understanding of structure-activity and structure-property relationships.
The next step of determining whether drug-drug interactions are involved is required for advanced lead optimization. The effect of drug transporters on permeability and the effect of drugs on transporter activity can be measured in Caco-2 for the impact on intestinal absorption or using relevant in vitro BBB models. P-gp interactions are particularly important for CNS drugs due to high expression of these efflux transporters in the human BBB. Early knowledge about these interactions is instrumental to the medicinal chemistry strategy and helps drive lead optimization. In vivo toxic effects on human cells can be predicted in vitro by measuring cytotoxicity using mammalian cell lines or primary cells. The effect of a compound on CYP450 metabolism can be identified by determining the 50% inhibitory concentration (IC50) for each CYP450 enzyme. These relationships between the NCE and metabolizing enzymes need to be evaluated in the context of the human effective dose and maximum effective plasma concentrations. These human data are not normally available at early stages of discovery, but could be extrapolated from animal PK/PD results for compounds in more advanced stages of development.
It is important to understand these transporter and CYP450 relationships for several reasons. First, the compound may affect the effective plasma concentrations of other drugs taken concomitantly with the compound of interest if they are metabolized by the same CYP450 enzymes (see the discussion of the terfenadine case above). Second, if the parent drug is a CYP450 inducer, it may increase the clearance rate of concomitantly administered drugs that are metabolized by these CYP450 enzymes. This may result in a decrease in these drugs' effective plasma concentrations, thus decreasing their pharmacological effect. Third, metabolites formed via CYP450 metabolism may be responsible for undesirable side effects such as organ toxicity. Fourth, the metabolite of a compound may actually be responsible for a compound's efficacy, and not the parent compound. The metabolite may even have a better efficacy, safety, and PK profile than its parent. If so, metabolism can be exploited to produce a better drug, which will substantially change the medicinal chemistry strategy. Fifth, the identification of drug-metabolizing enzymes involved in the major metabolic pathways of a compound helps in predicting the probable drug-drug interactions in humans. This information may also make human clinical trials designed to detect drug-drug interaction unnecessary, accruing a substantial cost savings in development.
ADMET is a tool that supports overall program goals. Seldom will negative results from a single ADMET assay kill a compound or a program. Remember, the Rule of 5 requires that only three of the four conditions be met, and even then there are exceptions. Instead, as was illustrated above in the case of metabolism, the results are more likely to just change the direction of the medicinal chemistry.
After assessing compounds in a few simple mechanistic systems such as plasma and liver microsomal stability screens in relevant species, one moves on to lead optimization using assays to identify potential liabilities. Finally, at the stage of advanced lead optimization and development, systems that are more complex are used to more thoroughly understand a compound's metabolic fate and absorption mechanism, and this understanding is used to drive efficient development. As ADMET roadblocks are discovered, which they inevitably will be, one repeats the loop until a clear path is found (Figure ).
Impact of ADMET
Early ADMET not only provides the data necessary for selecting preclinical candidates, by providing crucial information to medicinal chemists, it can also accelerate the timelines for IND and subsequently new drug application (NDA) submission, which means more time on the market under patent protection and hence greater profits. For investors, this is a major parameter. For philanthropic organizations and from the standpoint of public policy, it means increasing the time of clinical benefit to the public. Data compiled by the Tufts Center for Drug Discovery have identified that, for a typical, moderately successful proprietary drug (US$350 million annual sales), each day's delay equates to US$1.1 million in lost patent-protected revenues – revenues that provide the return on investment needed to fund drug discovery [3
]. Further, the shorter the discovery and development timelines are, the faster venture capital and angel investors can get to a liquidity event. As drug discovery takes longer to commercialize than any other form of product development, its slowness to produce returns is a major impediment for obtaining investment. Speeding up drug discovery and development should attract more investment in drug discovery research.
ADMET technologies remain a work in progress. There are many challenges in accurately measuring BBB penetration, which may be one of the reasons for poor human efficacy of CNS drug candidates. Another challenge is detection of all mechanisms of human idiosyncratic toxicity. These mechanisms cause the most expensive, harmful, and disheartening form of drug attrition – post-commercialization toxicity. Progress is being made. Many idiosyncratic drug reactions are due to formation of short-lived reactive metabolites that bind covalently to cell proteins [29
], and the extent to which a compound will generate these can now be detected before a compound reaches human patients. Other mechanisms of human toxicity can now also be detected early in discovery. Some of the assays that are available to detect them will be briefly described in the following section.