automation and robotics in adme screening

TECHNOLOGIES

DRUG DISCOVERY

TODAY

Drug Discovery Today: Technologies Vol. 1, No. 4 2004

Editors-in-Chief

Kelvin Lam – Pfizer, Inc., USA

Henk Timmerman – Vrije Universiteit, The Netherlands

Lead profiling

Automation and robotics inADME screeningKenneth C. SaundersAutomation Team, Department of Pharmacokinetics Dynamics and Metabolism, Pfizer Global Research and Development, Ramsgate Road,

Sandwich, Kent, UK CT13 9NJ

The use of automated sample processing, analytics and

screening technology for profiling absorption, distribu-

tion, metabolism and excretion (ADME) and physico-

chemical properties, early in the drug discovery

process, is becoming more widespread. The use and

application of these technologies is both diverse and

innovative. High-throughput screening (HTS) technol-

ogies have been utilised enabling the profiling of an

increased number of compounds emerging from the

drug discovery process. Although the drivers for using

these technologies are common, different approaches

can be taken.

E-mail address: (K.C. Saunders) [email protected]: http://www.pfizer.com/

1740-6749/$ � 2004 Elsevier Ltd. All rights reserved. DOI: 10.1016/j.ddtec.2004.11.009

Section Editors:Han van de Waterbeemd, Christopher Kohl – Pfizer GlobalResearch & Development, Sandwich Laboratories, PDM(Pharmacokinetics, Dynamics and Metabolism), Sandwich,Kent, UK CT13 9NJ

The increasing demand for high-quality ADME and physicochemical

data in early drug discovery have resulted in semi- or fully automatedrobotic systems for the measurement of the key properties in medium

to high-throughput. Based on many years experience in the field ofautomation and the bioanalysis of ADME samples, Ken Saunders

presents here the state-of-the-art in ADME screening technology.

Modern systems need to be balanced between good data quality, high-throughput, and flexibility to allow easy addition or removal of

particular assays. The move to automated high-throughput ADME datageneration system creates an increased demand for improved data

analysis tools and in silico predictive models.

Introduction

There is an increasing demand to profile more in vitro absorp-

tion, distribution, metabolism and excretion (ADME; see Glos-

sary) and physicochemical properties of newly synthesised

compounds early during a discovery program [1,2]. Chem-

istry departments in pharmaceutical companies have the

capacity to generate hundreds of compounds per day, thus

creating a requirement for innovative automated high-

throughput solutions to provide these data in a rapid manner.

Many different automated platforms have been developed

and the assays have been adapted to operate at high capacities

[3]. High-throughput liquid chromatography–mass spectro-

metry (LC–MS; see Glossary) has accelerated the development

of ADME assays in recent years and they tend to be configured

in micro-titre plate formats [4]. The sensitivity, selectivity and

speed of this technique have enabled samples from CYTO-

CHROME P450 (see Glossary) and permeability assays, such as

CACO-2 (see Glossary) and parallel artificial membrane permea-

tion assay (PAMPA; see Glossary), to be analysed.

Although work in this field has been focused on assay

miniaturisation and the analytical end-points, automating

the whole process has advantages including throughput,

robustness and release of resources. Automated systems have

been developed for single assays or a multiple assay process

[5]. All components of this type of ADME process can be

automated (sample submission through to result reporting).

Automation approaches

One of the emerging areas of robotics and automation is in

the profiling of in vitro ADME and physicochemical proper-

ties. Automation for use in drug metabolism and pharmaco-

kinetic (DMPK; see Glossary) studies can be exploited to varying

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Drug Discovery Today: Technologies | Lead profiling Vol. 1, No. 4 2004

Glossary

ADME: absorption, distribution, metabolism and excretion.

Caco-2 cells: human colon adenocarcinoma cells.

Cytochrome P450: major sub-family of isoenzymes present in the liver

responsible for the metabolism of drug-like compounds.

DDI: drug–drug interaction with respect to co-administered medication

and drug-metabolising enzymes such as cytochrome P450.

DMPK: drug metabolism and pharmacokinetics.

DMSO: dimethylsulphoxide.

HPLC: high-performance liquid chromatography.

HTS: high-throughput screening.

log D: the logarithm of the distribution coefficient at a certain pH.

log P: the logarithm of the partition coefficient at a neutral pH.

MALDI: matrix-assisted laser desorption ionisation.

MDCK: Madin Darby Canine Kidney cells.

LC–MS: liquid chromatography–mass spectrometry.

PAMPA: parallel artificial membrane permeation assay.

pKa: the ionisation constant for a particular compound.Figure 1. An example of a fully automated centralised robotic platform

used to for profiling in vitro ADME and physicochemical properties.

degrees [6]. Complex integrated systems are available that are

specialised for high-capacity and simple protocols. This type

of system is widely used in biological throughput screening

(HTS; see Glossary). The high sample capacity of these systems

is optimised for the vast compound numbers encountered in

biological HTS (i.e. multiple compounds per screen) [7].

ADME screens are configured for multiple screens per com-

pound and some of the assays cannot be miniaturised to use

this type of instrumentation. The most common approach

used in DMPK studies is semi-automated; this approach uses

individual workstations, such as 96-well instruments, and has

been established in many DMPK departments [8]. It has the

advantage of being flexible, enabling manual intervention at

the main stages of the assay for tasks that include loading

reagents and centrifugation. Unfortunately, this is also a

disadvantage because unattended operation is often pre-

ferred, particularly with respect to loading and preparing

samples for analysis.

An alternative approach reported is ‘‘industrial automa-

tion’’, which is used by companies such as Cyprotex (http://

www.cyprotex.com/), EvotecOAI (http://www.evotecoai.

com/), The Automation Partnership (http://www.automation-

partnership.com/) and other pharmaceutical companies. This

approach uses a combination of HTS technologies that have

been integrated into the relevant stages of the ADME screens,

such as plate replication, reagent addition and analysis. These

companies use leading-edge screening technologies to run

traditional in vitro ADME tests via a ‘‘HTS-like’’ process. This

approach can providea big increase in throughput and can also

reduce running costs (after the initial capital outlay).

A fully automated approach can be taken, using a centra-

lised robotic platform (or arm) integrated with ADME work-

stations, which can carry out single or multiple assays [9].

These systems are designed for fully automated sample pre-

paration, data analysis and management of results generated

374 www.drugdiscoverytoday.com

from in vitro ADME assays. Fully automated robots have also

been integrated with sample submission and the LC–MS

analytical systems [Green, C.E. et al. (2004) ALIAS: an auto-

mated laboratory in vitro assay system for candidate selection.

Abstracts of Papers ELRIG: Next Meeting on ADME Advances].

Systems with a centralised robotic arm combine a series of

modular assay work stations to provide a robotic platform,

which is flexible, upgradeable and easily reconfigured when

assays change or are newly developed (Fig. 1).

The scheduling and programming of these robots is key to

their success and unattended, parallel and overnight opera-

tion is routine. Facile sample submission and data reporting

‘‘on the fly’’ can be done remotely via a web interface.

Although the capital outlay for these systems is initially high,

the benefits of using less manpower, more time to visualise

the data and more efficient use of a scientist’s time are the

primary advantages. These systems give a fully integrated

approach to high-throughput ADME evaluation in support

of drug discovery.

Parallel approaches to both sample preparation and ana-

lysis are widely employed to improve throughput and effi-

ciency of in vitro ADME processes. Automated systems can be

programmed and scheduled to prioritise multiple tasks in a

procedure. These systems are also programmed and inte-

grated with analytical instruments, such as plate readers or

mass spectrometers, allowing unattended loading and ana-

lyses of samples.

Parallel approaches are most commonly employed with

LC–MS systems and analysis of samples generated from in

vitro ADME screens. Multiplexing both chromatography sys-

tems and ion sources are commonly used in this field. Multi-

ple samples (usually four or eight samples) are injected onto a

parallel LC system simultaneously and then analysed using a

parallel ion source [10]. Increased throughput can be

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Vol. 1, No. 4 2004 Drug Discovery Today: Technologies | Lead profiling

obtained by incorporating cassette experiments into the

assay protocol (whereby more than one compound is added

to the experiment at once) or sample pooling (cassette ana-

lysis strategies, see below). Mass spectrometers can monitor

multiple analytes simultaneously in a sample mixture with-

out significantly compromising sensitivity. This feature

enables the dosing of multiple compounds in certain experi-

ments and monitoring for all these analytes, which provides

significant gains in efficiency.

An alternative strategy is to combine the samples produced

for analysis at the end of the ADME experiment (sample

pooling strategy) [11]. Cassette and pooling strategies have

disadvantages, such as compounds interfering with each

other in either the experiment or the detection system.

Nonetheless, they can be applied successfully provided that

safeguards are put in place during the sample submission,

preparation and data acquisition processes.

Sample management and submission systems

The systems used for sample tracking and submission of

liquid or solid compounds in automated ADME is pivotal.

Most pharmaceutical companies now have liquid or solid

compound sample banks that allow compounds to be pro-

vided in a flexible micro-plate format with an identifying bar

code. The compounds must be submitted to the DMPK

laboratory in solid or liquid form and all the appropriate

information tracked and reported. This can be done in a

variety of ways using databases, sample banks and web sites,

which provide facile methods of sample submission. The

compound sample stock solutions are normally provided

in micro-titre plates in the form of low volume, concentrated

solutions in a solvent such as dimethylsulphoxide (DMSO; see

Glossary). The sample plates are then entered into the appro-

priate systems and processed accordingly.

LC–MS

High-performance liquid chromatography (HPLC; see Glos-

sary) coupled to mass spectrometry is the analytical techni-

que that is most widely used within this expanding area of

science and technology. LC–MS is ideally suited for pharma-

ceutical compounds owing to the typical compound physi-

cochemical properties and molecular weight. LC–MS can

accept small volume samples in a micro-titre format and

monitor multiple analytes in the same sample in complex

mixtures such as biomatrices. Furthermore, LC–MS does not

rely on the property of a compound for detection, such as a

UV chromophore or fluorescence. Mass spectrometers are

relatively large, expensive to purchase and costly to operate.

This issue has driven innovative research into the more

efficient use of LC–MS or replacement of this detection

technique with cheaper alternatives.

In summary, this technique is employed for in vitro ADME

analyses owing to its all-round capability to detect most

compounds, enhanced sensitivity, selectivity and ease of

automation when compared with traditional analytical tech-

niques. LC–MS in a high-throughput mode is the end-point

most commonly used to quantify the vast number of samples

generated from these screens. Innovative ways to both ana-

lyse and process these samples by LC–MS have been reported

[12,13]. Significant effort continues in this area to reduce

analysis times. This can be done in a variety of ways by

multiplexing, mixing samples, using fast chromatography

and HPLC column switching.

In this regard, analytic throughput has improved signifi-

cantly by shortening HPLC run time. Analysis times have

now been reduced to around 15 s per sample to assess ADME

properties, such as metabolic clearance in liver micosomes.

This is achieved by using fast gradient column switched HPLC

systems, which elute the analytes into the MS detector in a

very short time.

In accordance with quicker run times, fast, automated data

processing of the analytical MS data is a key component in

providing rapid turn around of data to discovery project

teams. The first part of the process is the rapid determination

of mass spectrometric parameters of each single compound

for quantification purposes [14]. Once the MS conditions

have been determined the samples are analysed and acquired

as efficiently as possible. The data can then be processed and

ADME results reported. This can be done in a number of ways

but customised automated software packages have been

developed to allow the processing and extraction of the

relevant information as quickly as possible [15]. The speed

of analysis can therefore be the key to the throughput of these

assays and new ionisation techniques are being researched to

allow samples to be analysed in less than a second using LC–

MS coupled to a matrix-assisted laser desorption ionisation

(MALDI; see Glossary) type ionisation source [Cole, M.J. et al.

(2004) Characterization and performance of MALDI on a

triple quadrupole mass spectrometer for analysis and quan-

titation of small molecules. Abstracts of Papers, 227th ACS

National Meeting ANYL-014]. This type of system has the

potential to eliminate the LC–MS analysis time as a bottle-

neck.

Physicochemical methods

Solubility

Compound solubility is one of the most important properties

measured at an early stage. Low-solubility compounds are

more difficult to develop and produce variable data from

screens, such as Caco-2 and lipophilicity. Therefore, a rapid

low-cost method for determining solubility before running

the more costly ADME screens is a useful tool.

Turbidimetry is an established method often used as a

quick and simple assessment of solubility [16]. Compounds

dissolved in DMSO are diluted with aqueous buffer and the

degree precipitation is measured. This method is robust but



consumes more material than laser nephelometry, which has

been shown to be a reliable and sensitive technique for the

measurement of kinetic solubility in 96-well or 384-well plate

format [17]. This process can easily be automated on a liquid

sample processor, such as a Tecan Genesis (Tecan, http://

www.tecan.com/).

Thermodynamic or equilibrium solubility is considered the

gold standard procedure for measuring solubility. This

method, although accurate, consumes far more compound

and requires over 24 h shaking or equilibration and therefore

has relatively poor throughput for screening purposes. As

such, this method is generally used on development com-

pounds where solubility and dissolution of the dose is more

important and there is more crystalline material available.

Other dedicated hybrid automated systems have been

developed by Sirius (http://www.sirius-analytical.com/) to

measure solubility, such the new CheqSol instrument. These

specialised instruments are optimised to measure and profile

solubility in high- to medium-throughput mode. Depending

on the scientists’ requirements, they also provide the flex-

ibility to use different approaches to assess solubility.

pKa (ionisation constant)

Measuring the dissociation constant(s) or the PKA (see Glos-

sary) of new discovery compounds can be an important

parameter when considering the charged state of compound

in the body, as this can affect the distribution, solubility and

permeability of the compound.

Potentiometric titration methods are well established

[18,19], but the amount of compound required and capacity

restrictions limit their use during early discovery. Hence,

alternative strategies have been used to allow more rapid

and automated screening using capillary electrophoresis

[20] or high-throughput pKa instruments [21] available from

CombiSep (Presearch, http://www.presearch.co.uk/) and Sir-

ius, respectively.

Lipophilicity

Distribution coefficient (LOG D; see Glossary) and partition

coefficient (LOG P; see Glossary) are the most common lipo-

philicity parameters determined in drug discovery. The data

generated are used to rank novel compounds in terms of their

lipophilicity and help predict parameters such as in vivo

permeability and metabolic stability. The assay involves mea-

suring the distribution of a compound between a lipophilic

phase, such as octanol, and an aqueous phase, such as water

or buffer, at physiological pH. The established approach is to

use the shake-flask methodology in which a compound is

partitioned and then quantified in an octanol-aqueous sys-

tem [22]. This process can be easily automated on a liquid

sample processor and quantification can be carried out using

HPLC–MS or HPLC–UV end-points. log D or log P has been

estimated with success using HPLC retention factors [23].


This determination is completely automated and involves

injecting compound solutions onto a reversed-phase HPLC

system, they are then separated using a lipophilic HPLC

column and detected using UV detection. Sirius provides

instruments that operate automated procedures measuring

both log P and pKa utilising titrimetric methodology [24].

This is considered a gold standard determination for pKa. Also

available are more sensitive and high-throughput instru-

ments that use a UV end-point. log P and pKa can both be

determined using these instruments and log D can then be

calculated from these measured values.

Permeability and drug absorption using trans-well assays

The most common high-throughput in vitro permeability

assays use either artificial membranes or cell-based trans-well

systems. PAMPA offers a fast robust and cost-effective method

for assessing the intrinsic permeability of novel discovery

compounds [25,26]. Phospholipids are added to an organic

solvent, typically dodecane, on a trans-well filter plate to

mimic an intestinal membrane. Compounds are dosed to

one side of the trans-well plate at physiological pH and the

apparent permeability is measured as flux across the lipid

layer over a period of over time. This assay is configured in a

96-well format and has been automated on a single work-

station (robotic liquid handler). The assay is easily automated

and the analysis performed using either a UV plate reader or

mass spectrometer. In pharmaceutical companies this type of

assay tends to be used during early discovery, in a high-

throughput configuration (rather than other cell-based

assays), as it has the ability to rank compounds in terms of

intrinsic permeability in a cost-effective manner.

In vitro ADME methods

Caco-2 (or MDCK) trans-well assay

The most established cell-based assay for estimating intest-

inal permeability uses the Caco-2 [27] or Madin Darby Canine

Kidney cells (MDCK; see Glossary) cell line. Caco-2 cells have

the advantage that they express a variety of transport systems

present in the human intestine. The cells must be cultured

and then grown on the trans-well filter plates before carrying

out the assay. The recommended culture time is 18–21 days to

ensure that all the necessary transporters are present. MDCK

cells can be used in a similar manner to Caco-2 cells and have

a shorter culture time (approximately five days), but have the

disadvantage in that they are ‘‘non-human’’ in nature. The

trans-well plates are used in either a 24-well or more recently

in a 96-well format. The permeability experiment is carried

out in a bi-directional mode to estimate the contribution of

any active transport processes. Compound is dosed to either

side of the trans-well plate chambers and the rate of transport

(Papp) is estimated after 1–2 h. Samples from the assay are

usually quantified using LC–MS, as each compound can

produce up to 20 samples for analysis. This assay has been

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Table 1. Comparison summary table

Technology 1 Technology 2 Technology 3 Technology 4 Technology 5

Name of type of

automation

approach

Semi-automated Automated system dedicated

to a single assay

Industrial automation

with HTS technologies

Fully automated centralised

robotic platform

Analytics: LC–MS with

automated data handling

Name of specific

technologies

with associated

companies

Tecan, Packard, Hamilton

(http://www.hamiltoncompany.com/)

Sirius, Tecan, Hamilton, Zymark

(http://www.zymark.com/)

Beckman Coulter

Pharma companies,

Cyprotex, TAP, EvotecOAI

& Velocity 11

(http://www.velocity11.com/)

Pharma companies, Cyprotex,

The Automation Partnership,

Hamilton & Zymark

Applied Biosystems/MDS

Sciex, Micro-mass,

custom solutions from Pharma

Pros � Redundancy and flexibility � Individual workstations

dedicated to an assay

� Use of leading-edge

robotic instrumentation

� Flexibility to perform

multiple tasks

� Specificity

� Adaptable approach to available budget � Gold standard measurements � Maximum data in early discovery � Unattended operation � Multi-analyte detection

� Parallel operation � Saving on staff resources � Robust to ADME samples

� Flexibility � Multi-plexing and sample pooling

Cons � Limited throughput � Less flexibility to perform

other assays on the

dedicated instruments

� Less flexible to change � Detailed programming

and scheduling

� Single approach

� Intensive use of manual resources � Poorer data quality � Long development times � Slow cf. plate-readers

� Instruments quickly outdated

Capacity

and Costs

� Lower capacity � Capacity limited for screening � HTS-like capacity and speed � High capacity � High capacity

� Cost-effective, manually intensive � Mid- to low-cost � High capital investment required � High initial capital and

infrastructure investment

� Instruments expensive to

purchase and operate

References [8,17,20,22,23,32] [19,21,24] [13,15,30,33] [9] [10–15,30,31]

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Related articles

Goodfellow, P. (2003) How automation can aid innovation in the pharma

industry. DDT 1017–1019

Chapman, T. (2003) Lab automation and robotics: Automation on the

move. Nature (Technology Feature) 421, 661–666

Smith, A. (2002) Screening for drug discovery. Nat. Rev. Drug Discov. 418,

453–459

Wang, J. et al. (2004) The impact of early ADME profiling on drug

discovery and development strategy. Drug Discov. World Fall, 77–86

Weiss A.J. (2003) Performing ADME earlier – a way to gain speed and

productivity. Business Brief.: Future Drug Discov. 1–3.

Links

� http://labautomation.org/: LabAutomation, conference and exhibition

on emerging laboratory technologies

� http://www.elrig.org/: European Laboratory Robotics Interest Group

automated on a number of platforms including Beckman

Biomek liquid handlers (Beckman-coulter, http://www.beck-

mancoulter.com/). Automating the assay procedure and

cell culture process and optimising the analytics have

enhanced the throughput. However, the disadvantages of

this method are the fairly complex process of automation

and high-throughput and the costs of producing the cultured

plates.

Metabolic clearance

Prediction of metabolic clearance from in vitro methods is one

of the main screening tools used by most ADME groups

[15,28]. Measurement of a discovery compound’s metabolic

stability in liver microsomes or hepatocytes can be a very

useful tool in predicting desirable drug-like properties [29].

Compounds are incubated with liver microsomes or hepato-

cytes and their disappearance measured over time, from

which the clearance can be derived. This type of assay has

been automated on liquid sample processors fitted with

suitable incubators that are programmed to sample at set

time points and the metabolism quenched with an organic

solvent, such as acetonitrile. Quantification is usually per-

formed using LC–MS.

Cytochrome P450 inhibition and drug–drug interactions (DDI)

assays

Compounds that are potent inhibitors of the major drug

metabolising enzymes (cytochrome P450s) can lead to drugs

that yield undesirable drug–drug interactions in the clinic

when co-administered with other medication. Therefore,

compounds are screened early in discovery to identify the

major metabolic pathways and any potential cytochrome

P450 inhibition. Assays are designed to monitor these poten-

tial DDIS (see Glossary) with human microsomes or recombi-

nant cytochrome P450 using specific probe substrates with

well-characterised metabolic pathways. New discovery com-

pounds are co-incubated with these test substrates and the

formation of metabolites monitored, allowing the assessment

of the any potential DDI. Traditionally this has been carried

out with quantification of the substrates and metabolites by

LC–MS [30] and the assay procedure can be easily automated.

A more recent development uses an ‘‘inhibition cocktail’’

approach for high-throughput inhibition screening of the

major human cytochrome P450 enzymes [31]. This assay is

configured using ascending substrate standard concentra-

tions (as a cocktail or mixture) for quantification, alterna-

tively a single substrate cocktail concentration may be used,

thus allowing even higher throughput. Fluorescence-based

approaches are now widely used [32] because these have the

advantage of high capacity with no requirement for the more

costly LC–MS analysis. This screen can be easily automated in

a 384-well plate format, as this set up is similar to many high-

throughput biological screens.


Conclusions

The increase in new chemical entities emerging from discov-

ery is a result of high-throughput medicinal chemistry, such

as parallel synthesis and the associated biological screening of

the compounds for potency. The recent strategy to define

ADME and physicochemical properties early on has driven

the requirement for high-capacity ADME assays [33].

Improvements in the capacity, speed and efficiency of the

drug discovery process are constantly being sought after in

the pharmaceutical industry.

The philosophy is that profiling these ‘‘drug-like’’ proper-

ties early on will identify potential development liabilities,

thereby increasing efficiency and reduce compound attrition

later on in a compound’s development (where the cost is

exponentially more) [34]. The modern paradigm of placing in

vitro ADME and physicochemical screens during early dis-

covery processes has led to increased pressures on ADME

groups to develop automated solutions that address the bot-

tlenecks in sample handling, analysis and data reporting.

These automated solutions and technologies have advan-

tages and disadvantages (Table 1). Although automated solu-

tions for in vitro ADME assays should in reality yield an

increase in capacity, accuracy, throughput, reliability and

lower costs, this might not necessarily be the case [35].

Laboratory automation will continue to shape the future of

in vitro ADME techniques used in early discovery. It will

continue to help optimise efficiencies using increased

throughput and miniaturisation. Miniaturisation and HTS

is continually pushing the boundaries of screening science

[7,36] and this will continue to impact this field in the future.

Implementation of automation gives benefits of throughput

and reliability. Automated systems can track samples

throughout the assay process (using bar-coding and database

technologies). They can also be much quicker, for example,

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Vol. 1, No. 4 2004 Drug Discovery Today: Technologies | Lead profiling

using micro titre plate technology. This is particularly true of

processes that can be done in parallel. Other advantages

include unattended (overnight) operation, better use of ana-

lytical resources, reduced inter-operator variability, and

releasing resources for other tasks. The development of sound

automated ADME and physicochemical procedures requires a

diverse skill set from computer programming to the hands on

science of DMPK. In vitro ADME procedures are often lengthy

and relatively complex because they require extensive opti-

misation to automate them. The trend nowadays is therefore

to use cheaper and simpler procures wherever possible, for

example, using a PAMPA screen rather than a Caco-2 assay for

high-throughput. ADME assays are relatively expensive in

terms of resources, reagents and detection techniques, and

hence it is too costly to screen every compound synthesised.

As a result, big pharmaceutical companies are using in silico

approaches in combination with (or in place of) these more

expensive automated in vitro systems.

Outstanding issues

� There is a limited amount of information or publications concerning

automation of ADME in vitro and physicochemical screening.

� In recent times, the focus on ADME in vitro and physicochemical

screening has switched to the more cost-effective and simpler assays.

� Scientists can be more focused on using the information generated

than developing the science and automated method.

� For greater efficiency a selective screening approach can be used, for

example, in vitro data generated from automated systems must be

used in combination with in silico approaches (in combo).

� Relative costs of the technology, particularly the reagents, robotics

and mass spectrometers has meant pharmaceutical companies can

become less willing to invest in automated approaches.

� A full evaluation of the variability of all the in vitro assays must be

carried out as binning strategies may have to be applied to the data,

which can mean in silico strategies, would provide a more cost-

effective option.

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