4 Drug Metabolism Assays and Their Use in Drug Discovery

M.K. Bayliss, P.J. Eddershaw

4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 69 4.2 Data Analysis and Computational Approaches to DMPK . . . . . . .. 71 4.3 In Vitro Approaches ..................................... 74 4.4 In Vivo Approaches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 76 4.5 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 78 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 79

4.1 Introduction

Arguably the biggest challenge currently facing the global pharmaceuti­cal industry is the urgent need for improvements in productivity in the discovery and development of new medicines. Improved productivity requires enhancements in both efficiency and effectiveness. Thus, in the context of drug discovery it involves a shortening of the time taken from lead identification to full development, but more importantly, a marked increase in the quality of drug candidates provided for development. The consequences of the past practice of taking sub-optimal compounds into development are all too apparent in the high attrition rate of drug candidates during this phase and the oft-repeated fact that the majority of the cost of bringing a new medicine to market is due to those failures (Abelson 1993).

The most obvious impact of these pressures is the wide-spread move within the pharmaceutical industry towards "front-loaded" drug discov-

O. Pelkonen et al. (eds.), Pharmacokinetic Challenges in Drug Discovery© Springer-Verlag Berlin Heidelberg 2002

70 M.K. Bayliss, P.J. Eddershaw

Fig. 1. Schematic representation of molecules with optimal balance of drug­like properties

ery. This entails the integration of what were previously development activities into the earlier phases of the discovery process. Nowhere is this more apparent than in the area of drug metabolism and pharmacok­inetics (DMPK). The lack of appropriate pharmacokinetics is a major contributor to the failure of many drug candidates during drug develop­ment. Problems such as low (and variable) absorption, insufficient sys­temic exposure or the potential for drug-drug interactions with co-ad­ministered therapies all reduce the clinic al and commercial viability of molecules (Fig. 1). For this reason, DMPK groups now play a key part in the identification and optimisation of lead molecules for subsequent development.

A major factor in the establishment of DMPK within drug discovery has been the relative ease by which traditional in vivo and in vitro technologies were able to be applied to the particular needs of drug discovery projects. Moreover, as will be described in this article, recent developments in automation and bioana1ysis have added further to our capabilities in this respect. However, there is stiH a need to replace the empirica1 nature of DMPK with a more rational, design-led approach if we are to achieve real improvements in efficiency and effectiveness. This requires a gre ater knowledge of the factors relating chemica1 struc­ture and properties such as absorption and drug disposition, as well as potency, safety and other aspects of developability in order to guide

PPB

Drug Metabolism Assays and Their Use in Drug Discovery 71

Poor systemic exposure Poor bioavailability Drug-drug interactions

Distribution

Volume of

distribution

Target tissue

c.,L" ;PM _'.0 ~ I r-:::"bili~ Eo_ Eo_ ~ I Gut st, induction inhibition

Renal Hepatic

Pgp Solubility

Metabolic Biliary Permeability

Fig. 2. Major absorption, distribution, metabolism and excretion/pharrnacoki­netic (ADMEIPK) issues encountered during lead optimisation. PPB, plasma protein binding; FPM, first pass metabolism

projects towards truly optimised candidates as quickly as possible (Fig. 2).

4.2 Data Analysis and Compntational Approaches to DMPK

Truly effective in silico approaches to predict drug absorption, distribu­tion, metabolism and excretion (ADME) have long been sought by DMPK scientists since they offer considerable advantages in time and effort over conventional in vivo and in vitro methods. Until recently, such attempts were confounded by a lack of suitable data on which to build robust models that had applicability beyond a given small series of molecules. This situation is now changing with the routine use of higher throughput methods for studying aspects of absorption and drug dispo­sition and an increasing awareness of informatics within the DMPK area.

In silico methods offer three key features for drug discovery. First, they can improve the design of molecules prior to synthesis, so-called virtual screening. This is particularly useful for combinatorial synthesis of large libraries of molecules where many combinations of monomers

72 M.K. Bayliss, P.J. Eddershaw

are added to a central scaffold. Assessment of these libraries for proper­ties such as absorption and CNS penetrability can help to identify monomers which consistently produce molecules which are unlikely to meet requirements in these areas. By omitting or replacing these mono­mers, the overall quality of the library and any subsequent active mole­cules resulting from it should therefore be improved.

Secondly, predictive models of key ADME properties can be used to prioritise compounds for further testing. A common bottleneck often encountered following primary activity screens is the requirement for subsequent activity and selectivity testing, either in a lower capacity in vitro system or an animal model. Computational models can provide an effective way of selecting the best compounds to be progressed, particu­larly when the number of compounds under consideration is too large for DMPK characterisation, or limited supplies of compound have to be retained for activity work. Although in vitro tests can also be effective at this stage, the ease with which computational systems can be run makes them an attractive alternative. In our laboratories, for example, this has led to the replacement of a cell-based in vitro system for measuring permeation-,with a computational approach to estimate likely human absorption. The cell-based assay used a monolayer formed from a Madin-Darby canine kidney (MDCK) cell line (Irvine et al. 1999) and required liquid chromatography/mass spectrometry (LC-MS) analysis to determine the amount of test compound able to pass from the apical chamber, across the cell monolayer to the basolateral chamber. The combination of a cell-based assay and LC-MS analysis resulted in a relatively labour-intensive system. Moreover, problems with achieving an adequate mass-balance, typical of such systems, meant that the generation of useful results for many compounds was often not possible in a reasonable time frame. The computational approach consists of two complementary models of human oral absorption: the Lipinski rule of five parameters (Lipinski et al. 1997) and an additional physico-chemi­cal model based on calculated log D and molar refractivity (an estimate of molecular size). If a molecule is classed as "OK", i.e. possessing characteristics indicating permeability, by both of these models, it is predicted as likely to have acceptable oral absorption. Analysis of data generated by both the in vitro and in silico approaches for about 1,000 compounds showed agreement of over 90% in identifying molecules with good permeability/absorption. In addition, the in silico approach

Drug Metabolism Assays and Their Use in Drug Discovery 73

was able to highlight compounds likely to be poorly 'absorbed to a greater extent than was possible with the in vitro system. Therefore, not only does the in silico system give comparable or possibly superior results, it is also much less demanding to operate routinely, allowing resources to be re-deployed on more specialised systems providing higher definition data.

The third and most important feature of in silico approaches is the ability to develop structure - property relationships for aspects of DMPK. As mentioned previously, this is a fundamental requirement of rational drug discovery, not only allowing the rationalisation of DMPK issues such as poor absorption or metabolic instability, but providing an indication of possible options to overcome them.

As DMPK has become established as a routine part of lead optimisa­tion, there is increasing interest in its role in the earlier stages of discovery. Once active molecules (hits) have been identified, the con­cept of template tractability becomes a key factor in selecting lead series to form the basis of optimisation programmes. This has typically centred on synthetic chemical considerations, together with indications of struc­ture-activity relationships (SAR) for the given target. It is becoming more common, however, to include aspects of drug absorption and disposition when assessing the best leads to progress. Here again, the advent of in silico approaches has proved extremely valuable in allow­ing a comparison of the drug-like properties of many compounds very quickly.

Whilst the assessment of the tractability of potential leads could be considered a key tenet of rational drug discovery, opinion is currently divided as to the actual value of this practice. It can be argued that the path of lead optimisation is determined largely by the drug -like qualities of the starting template and that the subsequent optimisation process can be streamlined by much earlier attention to factors such as safety and pharmacokinetics. Conversely, our lack of knowledge of the SAR sur­rounding DMPK factors could mean that a poor quality template can very quickly be transformed into a good one, or vice versa, through small chemical modifications. This is possibly the case for aspects such as metabolic stability but perhaps less so for absorption. It would cer­tainly appear a common experience that difficult lead series present a significant challenge to drug discovery projects and often fail to produce viable development candidates; one would hope that selection of a more

74 M.K. Bayliss, P.J. Eddershaw

drug-like starting point should minimise the number of iterations re­quired to produce a suitable drug candidate. As our ability to predict ADME in humans on the basis of physico-chemical and basic in vitro data advances, it should become possible to eliminate those apparent leads which in reality prove impossible or impractical to refine, and which currently waste much valuable resource.

4.3 In Vitro Approaches

The use of in vitro systems for studying metabolic stability and mem­brane permeation is commonplace in drug discovery. These systems are usually suitable for automation and thus present relatively high through­put approaches for identifying compounds for progression. A further advantage of such in vitro systems is the availability of human-derived or human-like materials which can provide additional insight into likely disposition in man.

The primary focus of in vitro systems for drug metabolism is rate. The aim is usually to identify those compounds which appear to be resistant to extensive metabolic attack and thus more likely to have sufficient exposure in vivo. The reverse may apply for topical or inhaled therapies where systemic exposure may lead to unwanted side-effects. For the screening process to be effective, it is necessary to establish a degree of correlation between the in vitro system and in vivo PK prop­erties, usually in an animal. Given the simplistic nature of in vitro systems mentioned earlier, it is unrealistic to expect absolute agreement with in vivo disposition. However, it is often possible to provide a broad categorisation of compounds according to their metabolic stability and to use this as a means of prioritising subsequent in vivo studies. It is important that in vitro screens are regularly validated against in vivo data to ensure that decisions based on in vitro data remain relatively sound, if not totally predictive, particularly as the chemical series evolve. The lack of an apparent correlation with in vivo disposition can sometimes highlight mechanistic factors such as the importance of phase II metabolism, cell permeation or protein binding which may be absent from the initial screen. A specific in vitro system could then be employed to target such factors.

Drug Metabolism Assays and Their Use in Drug Discovery 75

In addition to identifying compounds with low rates of metabolism, those compounds that are extensively metabolised can also be studied further to elucidate metabolic routes. This information is valuable in directing the chemical programme towards more stable molecules. Here again, the relative simplicity of an in vitro system and the ability to increase the concentration of the parent molecule offer advantages for the identification of primary metabolites. The widespread availability of recombinant human P450 preparations means that information on the enzymology of specific routes of metabolism can also be obtained during the drug discovery stage. Reliance on a single isoform for meta­bolic clearance can have implications for clinical use, particularly for isoforms such as CYP2D6 and 2C9 which display polymorphism in the human population. Moreover, knowledge of the SAR for the major human P450s provides further guidance in minimising extensive meta­bolism by these enzymes.

With most in vitro systems the requirement for liquid chromatogra­phy coupled with mass spectrometry (LC-MS) or LC-tandem mass spectrometry (MSIMS) limits their throughput. Despite this, it is possi­ble to achieve capacities of up to several hundreds of compounds studied within 1-2 weeks (Eddershaw and Dickins 1999). Alternatively, assays for measuring the potential to inhibit P450 metabolism are available which use pro-fluorescent probes and allow simultaneous rapid analysis of compounds using a fluorescence plate-reader (Crespi et al. 1997).

Although much emphasis has been placed on the throughput of in vitro systems, even low throughput systems can provide valuable infor­mation to discovery projects. The absence or control of factors such as blood flow, protein binding, pH and co-factor availability means that specific mechanistic issues can be isolated and studied in detail. It is important in supporting effective decision making in drug discovery that a sound understanding of the ADMEIPK issues impacting a given pro­ject is obtained wherever possible. A good example of this principle is provided by a recent lead optimisation project within our laboratories. The PK of over 30 compounds was determined in rat, with all but 2 compounds showing poor bioavailability. The clearance of all the mole­cules was low to moderate, which suggested that the bioavailability was limited by absorption from the gastrointestinal (GI) tract. Examination of the physico-chemical properties of the series identified several mole­cules likely to be poorly absorbed, but this did not explain the majority

76 M.K. Bayliss, P.J. Eddershaw

of compounds which were predicted to be well absorbed but showed poor bioavailability. The compounds were examined in an in vitro permeation model using a cell line expressing the P-glycoprotein (Pgp) efflux system. This system showed that all the compounds with poor bioavailability were substrates for Pgp, whereas the two compounds with acceptable bioavailability were not. This very clearly identified the nature of the problem and allowed further chemical effort to focus on minimising the impact of Pgp on bioavailability.

4.4 In Vivo Approaches

Despite the continuing improvement of computational and in vitro methods, the use of in vivo animal models remains the definitive method for studying pharmacokinetics during drug discovery. It is only through such studies that the combined impact of the myriad processes affecting drug absorption and disposition can be observed. However, the use of in vivo models is constrained by both ethical and practical factors. There is a widespread desire, reflecting public concern over animal rights, to reduce the use of animals for research purposes. In addition, animal studies are traditionally costly in terms of staff and facilities, relatively time consuming and often require significant amounts of compound. The impact of these factors on drug discovery projects has been reduced through the development of cassette dosing approaches. Cassette dosing is now an established method within the pharmaceutical industry, since it provides a relatively quick way of ranking compounds according to their pharmacokinetic properties and requires the use of fewer animals (Frick et al. 1998).

The full potential of cassette dosing has awaited the development of powerful analytical techniques such as HPLC coupled with tandem mass spectrometry (HPLCIMSIMS) (Korfmacher et al. 1997). The co­administration of several compounds exacerbates the problems nor­mally associated with the analysis of drugs. In addition to the problems caused by the interference of endogenous materials, cassette dosing increases the demand for selectivity of detection, since the multiple compounds and/or their metabolites may also co-elute and interfere with each other. The need to administer lower doses of the individual compo­nents in order to avoid pharmacological overdose and the potential for

Drug Metabolism Assays and Their Use in Drug Discovery 77

drug-drug interactions places an additional burden on the sensitivity of assays. For these reasons, cassette dosing depends greatly on the multi­ple reaction monitoring (MRM) technique afforded by tandem mass spectrometry.

In addition to the analytical requirements arising from cassette dos­ing, significant logistical challenges also need to be addressed. Most notably these are the design and formulation of the dose cassettes and the data reduction and processing following analysis.

In our hands, computer-aided approaches to various steps in the process have been crucial to the utility of cassette dosing. Tasks that took hours, such as designing the cassettes, can now be done in one or two minutes. The appropriate design of cassettes is vital, in order to reduce the likelihood of analytical interference in the mass spectrometer from compounds sharing the same molecular weight or likely to give rise to metabolically-derived clashes.

Processing of the data obtained from MS analysis is especially com­plex when large numbers ·of compounds are involved. Automatic trans­fer of data to a spreadsheet provides greater processing power than is typically available with commercial MS data systems. Custom built algorithms to derive concentrations of each the components of the cassette can then be applied and the resultant data exported to a pharma­cokinetic software package.

As with the use of computational or in vitro methods for ADME, cassette dosing requires validation against discrete in vivo PK studies. Provided a reasonable correlation exists, the need for discrete in vivo studies can be minimised. Very often, a "top and tail" strategy is possible whereby discrete studies are used at the beginning of a lead optimisation programme to characterise the PK properties of early templates and then later to provide definitive data on promising molecules approaching candidate selection. The bulk of the lead optimisation process concerned with ranking compounds for further progression can then be efficiently served by appropriate use of in silico, in vitro and/or cassette dosing methods. Where the use of cassette dosing is not found to be valid, automation of the pre- and post-in life stages of discrete PK studies also reduces the time and effort required to conduct such work (Watt et al. 2000).

78 M.K. Bayliss, P.J. Eddershaw

Fig. 3. Effect of in silico and in vitro methods on compound failure in devel­opment. Retrospective analysis performed on compounds studied at GlaxoW­ellcome over a 10- to -12-year period

4.5 Conclusions

Rational drug discovery requires an appraisal of ADMEIPK issues alongside other "develop ability" factors from the earliest stages of drug discovery. An integrated approach involving the various computational, in vitro and in vivo methods outlined in this article offers an effective means of producing good quality drug candidates with the balance of properties necessary for clinical efficacy. A retrospective analysis of compounds which had been lost during the drug development phase at GlaxoWellcome over the last 10--12 years shows that three quarters of these molecules would have been flagged as poor using a combination of the computational and in vitro approaches now routinely in use (Fig. 3).

ADMEIPK considerations are now being included in the generation of tractable hits at the early stages of drug discovery. This process, which has benefited from the development of high-quality computa­tional models of ADMEIPK properties, reflects the gradual change from

Drug Metabolism Assays and Their Use in Drug Discovery 79

an empirical science to a conceptual one based on greater understanding of the underlying principles governing drug absorption and disposition. It remains to be seen whether this change is sufficient to bring about the required improvements in productivity necessary for drug discovery organisations to remain viable.

Acknowledgements. The authors would like to acknowledge the contribution of the GlaxoWellcome Combinatorial Lead Optimisation Project (CLOP) team and the Research support Drug Metabolism Group.

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