[Methods and Principles in Medicinal Chemistry] Hit and Lead Profiling Volume 43 ||...

17Hematotoxicity: In Vitro and Ex Vivo Compound ProfilingDavid Brott and Francois Pognan

17.1Introduction

Thepharmaceutical industry spent approximatelyU.S.$ 35billion in2007 for researchand development. This is an approximate 12-fold increase from the 1980 level, but thenumber of new chemical entities (NCE) remained flat over this time period. Thisdecreased productivity is a major concern and could be due to several factors,including late-stage attrition rate increasing from 50 to 89% during drug develop-ment [1]. The majority of safety-related attrition occurs preclinically with approxi-mately 30% of attrition being due to toxicology and clinical safety [2]. Significant focusof the industry has been to improve compound selection during discovery to decreasepreclinical and clinical attrition, most noticeably by perfecting pharmacologicalefficacy and drug disposition and pharmacokinetics parameters. A new trend is nowemerging in which assays to profile toxicity side effects may also be used for this earlycompound selection. Here we will call �front-loading� this concept of using in vitroassays that mimic in vivo known and observed toxicities for the profiling and selectionof chemical series or specific chemicalswithin a series.Additional tools suchas in silicoexpert systems for the prediction of toxicity, based on in vitro and in vivo observations,are also used to the same end. In vitro compound profiling and in silico expert systemsmay lead to the discovery of potential biomarkers which can be used after somevalidation in preclinical and clinical studies.Themain target organs for compound toxicity leading to either drugwithdrawal or

arrest of compound development as estimated in various studies [3], are classicallypointing at liver, the cardiovascular system and bone marrow (hematotoxicity).Cardiovascular and hepatotoxicity were discussed in previous chapters and thischapter focuses on hematotoxicity.Hematotoxicity, defined as drug-induced altered production of peripheral blood

cells, ismost commonly associated with antiproliferative oncology compounds but isalso caused by drugs for various indications, covering a wide pharmacology andchemical structure diversity (Table 17.1). This vast variety of chemical structuresmakes it difficult to predict hematotoxicity by in silico approaches and to model

Hit and Lead Profiling. Edited by Bernard Faller and Laszlo UrbanCopyright � 2009 WILEY-VCH Verlag GmbH & Co. KGaA, WeinheimISBN: 978-3-527-32331-9

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Table 17.1 Compounds fromdifferent therapy areas, pharmacologicalclasses and structures that induce hematotoxicity [59–63].

Therapy area Compounds

Analgesic andanti-inflammatory

Acetylsalicylic acid, aminopyrine, benoxaprofen, dipyrone, bucilla-mine diclofenac, diflunisal, fenoprofen, ibuprofen, indomethacin,mefenamic acid, mesalazine, naproxen, pentazocine, phenylbuta-zone, piroxicam, quinine, sulindac, tolmetin

Anticonvulsant Carbamazepine, ethosuximide, lamotrigine, mesantoin, phenytoin,trimethadione, valproic acid

Antipsychotics,antidepressants

Amitriptyline, chlordiazepoxide, chlorpromazine, clomipramine,clozapine, cyanamide, desipramine, diazepam, dothiepin, doxepin,fluoxetine, haloperidol, imipramine, indalpine, levomepromazine,maprotiline, meprobamate, methotrimeprazine, mianserin, mirta-zapine, olanzapine, perazine, phenothiazines, phenelzine, quetia-pine, remoxipride risperidone, thioridazine, thiothixene, tiapride,trazodone, ziprasidone

Anti-infectives Abacavir, amodiaquine, amoxicillin-clavulanic acid, ampicillin, carbe-nicillin, cefamandole, cefepime, cefotaxime, ceftriaxone, cefuroxime,cephalexin, cephalothin, cephapirin, cephradine, chloramphenicol,chlorogunide, clarithromycine, clindamycin, cloxacillin, dapsone, dox-ycyclin, flucytosine, fusidic acid, gentamicin, griseofulvin, hyrdorxy-cloroquine, imipenem-cilastatin, indinavir, isoniazid, levamisol, linco-mycine linozilide,mebendazole,mietronidazoleminocycline, nafcillin,nifuroxazide, nitrofurantoin, norfloxacin, novobiocin, oxacillin, peni-cillin G, pernicillin G-procaine, piperacillin, pyrimethamine, quinine,ristocetin, rifampin, streptomycine, terbinafine, thiacetazone, ticarcil-lin, trimethoprim-sulfamethoxazole, vancomycin, zidovudine

Cardiovascular Acetyldigosin, ajmaline, amiodarone, aprindine, bepridil, bezafibrate,captopril, dinepazide, clopidogrel, coumarins, diazoxide, digoxin,dipyridamole, disopyramide, doxazosin, enalapril, flurbiprofen, fur-oxemide, hydralazine, lisinopril methyldopa, metolazone, nifedipine,phenindione, procainamide, propanolol, propafenone, quinidine,ramapril, spironolactone, thiazide diuretics, ticlopidine, vesnarinone

Gastrointestinal Cimetidine, famotidine, mesalazine, metiamide, metoclopramide,omeprazole, pirenzepine, ranitidine

Antihistamine Brompheniramine, cimetidine, methapheniline, methylthiouracil,mianserin, ranitidine, thenalidine, tripelennamine

Antithyroid Carbimazole, mithimazole, potassium perchlorate, potassium thio-cyanate, propylthiouracil

Other drugs Acetazolamide, acetosulfone, acetylcysteine, acitretin, allopurinol,aminoglutehimide, benzafibrate, brompheniramine, calcium dobe-silate, chloropheniramine, chlorpropamide, colchicine, deferiprone,dapsone, flutamide, glibenclamide, hydroxychloroquine, mebhydro-lin, meprobamate, metapyrilene, methazolamide, metochlopramide,prednisone, promethazine, retinoic acid, riluzole, ritodrine, tolbuta-mide, yohimbine

416j 17 Hematotoxicity: In Vitro and Ex Vivo Compound Profiling

predictive in vitro assays. Therefore, historically, hematotoxic potential of compoundswere first evaluated during drug candidate nomination in vivo studies bymicroscopicevaluation of bonemarrow cellularity from decalcified bone smears, hematology andin some cases bone marrow differentials. Identification of bone marrow toxicity inthese in vivo studies may result in late-stage nonclinical attrition when clinicalindications may not tolerate such untoward effects or when the safety marginbetween the therapeutic effect and the first observed bone marrow side effects aretoo narrow. For example, a drug for asthmamust have very stringent toxicity criteria,while an anticancer treatment could tolerate much higher risk. However, evenanticancer drugs are now improving their whole range of undesirable side effectsand it is clear that, all other parameters being equal, an anticancer molecule with abetter hematotoxicity profile is favored by the pharmaceutical industry as well as bythe regulatory authorities, clinicians and patients.This late-stage attrition due to bone marrow toxicity can be reduced if chemical

compounds in early stages of research can be profiled with relative confidence beforereaching development. For clear reasons of throughput, material quantities, cost andreduction of animal use issues, in vivo studies are not convenient for such ahematotoxicity front-loading. Hence, the solution can only be in the use of in vitroassays reflecting more or less accurately the in vivo biology of bone marrow.Therefore, prior to developing front-loading assays to evaluate target-related orchemistry-induced hematotoxicity, the general pathophysiological pathways of he-matopoiesis must be understood. Hematopoiesis, the production of blood cells, is acontinuum of blood-forming cells from pluripotent stem cells to multipotent stemcells and ending with the mature blood cells from the following lineages: lympho-cytes, myelocytes (neutrophils, eosinophils, basophils), monocytes, nonnucleatedred blood cells andmegakaryocytes that produce platelets. This continuum of cells inthe various lineages entails cellular proliferation, maturation and interactions withstromal cells, cytokines and hormones, and depending on duration and severity,interruption with any of these processes can result in hematotoxicity. The nextparagraphs describe compounds known to induce clinical hematotoxicity and variouspotential mechanisms.

17.2Known Compounds with Hematotoxic Potential

The goal in profiling compounds early in drug discovery is to predict clinical outcomealso known as adverse drug reaction (ADR) for compounds. In clinical studies, bonemarrow toxicity is quantified by hematology analysis of peripheral blood with themajor toxicities being agranulocytosis/neutropenia, thrombocytopenia and ane-mia [4]. Therefore, screening assays and cascade should predict these clinicalhematology changes. Prior to developing such assays, pharmacological and struc-tural characteristics of compounds that induce hematotoxicity and the variousmechanisms of these compounds need to be understood. The most recognizedclass of compounds that induce clinical bonemarrow toxicity are the antiproliferative

17.2 Known Compounds with Hematotoxic Potential j417

oncology compounds, since these general cytotoxins destroy proliferating cells andbone marrow is a highly proliferative tissue. However, some non-antiproliferative(non-oncology) compounds are also known to induce bone marrow toxicity in theclinical setting.Table 17.1 lists non-oncology compounds from diverse therapeutic, chemical,

pharmacological areas and structures that induce clinical hematotoxicity. Thisdemonstrates that bone marrow toxicity is not restricted to a small number ofpharmacological or structural classes, thereby making it more difficult to under-stand specific mechanisms of toxicity. However, there are three classes of mechan-isms of hematotoxicity, including antiproliferative, immune-mediated and other.Immune-mediated hematotoxicity and other indirect toxicities (e.g., a decrease oferythropoietin in kidney, leading to an impeded red cell production in the bonemarrow) are not discussed in detail in this chapter as it requires involvement of theimmune system or remote interactions and in vitro profiling assays have not beendeveloped to detect these mechanisms.Antiproliferative compounds are easily detected using cell line or colony-

forming unit (CFU) assays. Some of the potential mechanisms of non-antipro-liferative compounds leading to bone marrow toxicity include mitochondrialdysfunction [5, 6], aromatic hydrocarbon receptor (AhR) activation, receptor-mediated, altered receptor expression [7] and reactive intermediates [8, 9], butthis list may grow with additional research as the mechanism(s) leading to bonemarrow toxicity is still unknown for many compounds and will require significantamount of effort to elucidate. The next paragraphs briefly describe these potentialmechanisms.In many ways, mitochondria resemble bacteria; for example, the mitochondrial

ribosomal RNA genes of all eukaryotes have been traced back to the eubacteria [10].This can explain why some antibacterial compounds with the target of inhibitingbacterial protein synthesis also inhibit mitochondrial protein synthesis [6, 11, 12],resulting in hematotoxicity. Tetracycline, chloramphenicol and some oxazolidinoneantibiotics have been shown to induce hematotoxicity by inhibiting mitochondrialprotein synthesis [13].The AhR is expressed in bonemarrow stromal cells [14] and humanhematopoietic

stem cells [15] and upon agonist binding the receptor translocates to the nucleus,resulting in altered transcriptional expression such as increased CYP1A1 [16] andresulting in reactive oxygen species [17]. Nonpharmaceutical compounds such asTCDD, benzo(a)pyrene and benzene have been shown to induce hematotoxicityusing this mechanism in vivo and in vitro [18, 19].In addition to oxygen free radicals, other compounds such a clozapine, olanzapine

and procainamide induce reactive intermediates [8, 9]. Clozapine and olanzapinebioactivation is thought to occur through a nitrenium ion [20]; however clozapine butnot olanzapine induce toxicity to neutrophils. This can lead to an immune-mediateddepletion of neutrophils and their precursors (CFU-GM) [21]. Also, nonsteroidal anti-inflammatory drugs (NSAIDs) have pro-oxidant radicals that when metabolizedcould cause oxidative stress [22].


Primary or secondary pharmacology can influence hematopoiesis becausehematopoietic and stromal cells express many different receptors that are alsotherapeutic targets, such as neurotransmitters [23–25]. In themouse, anH1 receptoragonist antagonized theH2-induced increase ofCFU-GMby its off-target effect at thelatter receptor [26]. Albeit this is not an example of direct hematotoxicity, it doesdemonstrate that therapeutic drugs bind to targets on hematopoietic and stromalcells and influence hematopoiesis.The last potential mechanism to be discussed in this chapter is drug-induced

altered receptor expression.Hematopoiesis is a very intricate process that is regulatedby cytokines and cell–cell interactions. Interruption with any of these processescan result in hematotoxicity. For example, zidovudine (AZT) decreases Epo [27],GM-CSFaand to lesser extent IL-3 receptor expression [7].Decrease in the expressionof the above receptors seems to lead to anemia and neutropenia, by decreasing thenumber of CFU-E and CFU-GM, respectively.Although not a mechanism of hematotoxicity, polymorphic metabolism of a

compound needs to be discussed since polymorphism can be associated with clinicalhematotoxicity. For several compounds [28–39], one of the polymorphic enzymesincreases exposure to the toxic form of the compound and thereby induces hema-totoxicity in the patient, due to higher exposure levels and not due to a specificmechanism of toxicity within the patient populations.

17.3Tiered Cascade of Testing

Over the past years in vitro assays, such as the colony-forming unit (CFU) assay, havebeen qualified for predicting in vivo toxicity and these assays now permit front-loading evaluation of bone marrow toxicity potential of compounds. The differentCFU assays described below, present many advantages, not least that they utilizeprimary bone marrow cells, have a relatively good validation history and gainedpopularity in the pharmaceutical industry. Nonetheless several drawbacks, mostnoticeably the low throughput and the need for experts and their relative objectivityfor reading the assays, made it necessary to develop more advanced and comple-mentary techniques.The next paragraphs describe several assays of various throughput and automa-

tion, using cell lines and primary cells of various species used in toxicology, ableto deliver complementary information, as well as more mechanistic methodsbased on in vivo material, developed by the present authors and others. For theoptimal use of these techniques, we have ordered them in a three-tiered logicalcascade from �high throughput–low information� to �low throughput–highinformation.� This approach for evaluating hematotoxicity from target identificationthrough candidate nomination is discussed in detail in the following sections,together with the limited validation compound set used for assessing their viabilityand predictive value.

17.3 Tiered Cascade of Testing j419

17.3.1Tier 1 Tests

To screen for bone marrow toxicity early in drug discovery, assays must be able toevaluate hundreds of compounds, be inexpensive, report results within two weeks(in order to impact chemistry cycle times) and be able to detect toxicity irrespective ofcytotoxic or cytostatic mechanisms. Only cell line-based assays can meet all of thesevarious criteria.Brott et al. [40, 41] evaluated bone marrow toxicity to myeloid, erythroid and

stromal lineages usingmouse cell lines. Several cell lines were actually evaluated andthe present authors selected the M1 myeloid line (ATCC TIB-192), the HCD57erythroid line (a generous gift from Dr. Hankins [42]), the lymphoid line M-NFS-60(ATCC CRL-1838) and the stromal line M2-10B4 (ATCC CRL-1972). The nonhema-topoietic line HepG2 (ATCC HB-8065) was used to evaluate general cytotoxicity andas a control to enhance the predictive value of the assay. The concentration thatdecreased the cell number by 50% (IC50) was calculated for each of the cell lines andused to determine whether a compound was a bone marrow toxicant. A compoundwas deemed negative if it had an IC50 >100mM for all cell lines; a �potentiallypositive� compound had an IC50 �1mM and <100mM for at least one bone marrowcell lineage; and a �positive� compound had an IC50 <1mM for at least one celllineage. The goal of the assay was to influence chemistry until a best possiblecompound(s) or series of compounds could be progressed by the project team.However, if a projectmust progress a �potentially positive� or a �positive� compound,then this compoundmust be evaluated in tier 2 assays to determine species specificityand relevance of tier 1 results using primary bone marrow cells.When developing a medium- or high-throughput assay, the method by which the

assay is quantified is extremely important. For the various mouse cell lines inthe medium-throughput bone marrow tier 1 assay, there was linearity between cellline number and luminescence evaluated using the ATP reagent CellTiter Glo atthe time of culture initiation and at 24, 48 and 72 h of culture for each cell line(Figure 17.1). Optimal assay culture time for each cell line was based on cell linedoubling times with increased luminescence between culture initiation and harvesttime. The assay parameters for each cell line are shown in Table 17.2.Tier 1 assay qualification entailed: (i) evaluating compounds known to induce

lineage specific hematotoxicity; (ii) comparing the results from the myeloid tier 1assay to themouse CFU-GMassay; (iii) comparing the results from the erythroid tier1 assay to reduction in peripheral blood reticulocytes.The tier 1 assay accurately predicted in vivo lineage specific hematotoxicity and

general cytotoxicity (Table 17.3) with the erythroid cell line having the lowest IC50

value for the erythrotoxicant chloramphenicol and the myeloid cell line having thelowest IC50 values for the myelotoxicant methotrexate. These results documentedthat the cell lines did not detect general cytotoxicity, but were able to quantify lineagespecific toxicity similar to in vivo. In addition, compounds were evaluated severaltimes within the assay and showed good reproducibility (Figure 17.2) for a medium-throughput screening assay.


Table 17.2 Tier 1 assay conditions. Cell lines and optimal cultureconditions for evaluating bone marrow toxicity potential ofcompounds early in drug discovery. The adherent cell linesM2-10B4 and HepG2 are allowed to adhere to plates (preculturetime) prior to addition of test compound. Relative cell numberwithin a well is evaluated after the culture time using CellTiter Glo.

Lineage Cell line Media Mediaadditives

Cellsseeded

Type Preculture Culturetime

Myeloid M1 RPMI-1640

10%FBS,Pen/Strep

4000/well Non-adherent

0 h 72 h

Erythroid HCD57 IMDM 30% FBS,Pen/Strep,L-glutamine,100 pg/mLrmEpo,20 mM b-ME


0 h 72 h

Lymphoid MNFS60 RPMI-1640

10%FBS,Pen/Strep,62 ng/mLrhM-CSF,50 mM b-ME


0 h 48 h

Stromal M2-10B4 RPMI-1640

10%FBS,Pen/Strep

2000/well Adherent 24 h 72 h

Nonhemato-poietic

HepG2 DMEM 10%FBS,Pen/Strep

2000/well Adherent 24 h 72 h

Abbreviations: b-ME: beta mercaptoethanol; DMEM: Dulbecco�s modified Eagle�s medium; FBS:fetal bovine serum; IMDM: Iscove�s modified Dulbecco�s medium; Pen/Strep: 1� penicillin/streptomycin; rhM-CSF: recombinant human macrophage-colony stimulating factor; rmEpo:recombinant murine erythropoietin.

Table 17.3 Tier 1 assay qualification using compounds known toinduce lineage specific toxicity. The five compounds are evaluatedusing the optimal culture conditions for each of the cell lines(n¼ 3 experiments with triplicate wells within each experiment).The lowest IC50 for each compound corresponds to the expectedBM toxicity.

Compound ExpectedBM toxicity

Micromolar inhibitory concentration 50% (IC50)

Myeloid Erythroid Lymphoid Stromal Nonhematopoietic

Acebutololhydrochloride

None >100 >100 >100 >100 >100

Methotrexate Myeloid 0.005 >100 0.2 0.05 >100Chloramphenicol Erythroid >100 8 >100 81 >100Taxol Myeloid 0.009 2 0.03 0.9 40Camptothecin general <0.003 0.7 0.04 0.06 0.9


To further qualify the myeloid tier 1 assay, the myeloid cell line IC50 valueswere compared with the mouse CFU-GM IC50 values using compounds of verydiverse structures and targets (Figure 17.3). The mouse CFU-GM assay was used asthe comparator since this assay is known to detect compounds that will induceneutropenia, decreased number of peripheral blood myeloid cells. The two assayscorrelated well (r2¼ 0.80), indicating the tier 1myeloid assay was able to quantify thepotential of compounds to induce neutropenia. However, this was done withcompounds that had very diverse structures and targets and during drug discoverythe assay would be used to rank many compounds from one target and withpotentially similar core chemistry. To determine whether the myeloid tier 1 assaywas able to distinguish hematotoxicity of similar chemistries, 13 compounds withsimilar core chemistry were evaluated in both the tier 1 and the mouse CFU-GMassays (Figure 17.4). The two assays correlated well (r2¼ 0.74), qualifying the tier 1myeloid assay for evaluating compounds of similar chemistry early in drug discovery.Qualification of the erythroid tier 1 assay was more difficult as there are fewer

compounds known to induce in vivo erythrotoxicity and theCFU-E assay has not beenused to predict in vivo toxicity potential of compounds. Instead, the erythroid tier 1assay was qualified by comparing IC50 values with the percent peripheral bloodreticulocyte reduction using 16 AstraZeneca compoundswith similar core chemistry(Figure 17.5). When plotting the results from 15 compounds, r2¼ 0.83.Qualification of the tier 1 assays with the limited number of compounds indicated

that the cell lines were able to predict the in vivo hematotoxicity potential ofcompounds, but further qualification using more compounds and specificallynoncytotoxic compounds are still required.

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4 hour 24 hour 48 hour 72 hour

100 1000

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10000 100000

Figure 17.1 Correlation of cell number withluminescence and expansion of cells over 72hours. Various number of myeloid (M1) cellswere seeded at t¼ 0 and evaluated usingCellTiterGlo at the designated times. Therewas alinear correlation between cell number seededand luminescence (4 h time point) indicatingCellTiter Glo is adequate to evaluate relative

number of cells in a well. Luminescenceincreased between 4 and 72 h at almost allseeding densities. N¼ 3 experiments withtriplicate wells in each experiment. Althoughnot shown, the erythroid (HCS57), lymphoid(M-NFS-60), stromal (M2-10B) and non-hematopoietic (HepG2) cell lines had similarresults.


As powerful or predictive as these assays can be, an ordinate and ingenious use ofthem is necessary for optimal impact on drug development. As described above, themouse cell line screening assay allows a fast and relative prediction of bone marrowtoxicity of known toxicants in vivo (positive controls of the validation set). Moreinterestingly, it allows to rank order chemical series and chemicals within a series.The simplicity of the assay itself, the low cost, its possible automation and the fastturnaround of data generation makes it an ideal tool to profile large numbers ofcompounds. Hence, this step can be used at relatively early stages of drug discovery.The whole assay can be streamlined with automatic cell culture and maintenance,linked to robotic stations and multiplate reader analysis to measure the ATP content

Figure 17.2 Reproducibility of compound concentration thatdecreases relative cell number by 50% (IC50). Each data pointis based on the IC50 from a 12-point titration curve of eachcompound. N� 3 experiments with triplicate wells within eachexperiment.


Figure 17.3 Tier 1 myeloid assay (M1 cell line)qualification using known hematotoxicants ofdifferent chemical pharmacology and structure.Fifteen compounds with either known colony-forming unit granulocyte-macrophage(CFU-GM) IC50 values from literature or

evaluate in-house were compared to IC50

from level 1 myeloid cell assay. n¼ 3experiments with triplicate wells within eachexperiment. The linear regression line isplotted showing the correlation between thetwo assays.

Figure 17.4 Tier 1 myeloid assay (M1 cell line)qualification using compounds of similarchemical pharmacology and structure. Thirteencompounds from a single core structure wereevaluated in the tier 1 myeloid assay (n¼ 1

experiment with triplicate conditions) and35mm dish CFU-GM assay (n¼ 1 experimentwith triplicate plates). The linear regression lineis plotted showing the correlation between thetwo assays.


by luminescence. With such a set up, a large volume of data can be generated rapidlyenough to orientate the chemistry in one direction or another. This process can beiterative, back-and-forth between bone marrow toxicity profiling and new chemistrysynthesis. This should in principle allow sufficient refining of the drug candidates tobe devoid of hematotoxicity if not directly linked to pharmacology, or at least to atolerable level and not impede further drug development up to the patients.Interestingly, it is not unusual for chemical series to be fairly toxic on the erythroid

cell line, for example, while having no effect at all on the white cell lineages, or thestromal lineage, or any other combination. However, while optimizing the chemistryto reduce the erythroid lineage toxicity, other lineage toxicity might arise. Hence, itcan be difficult to choose the proper chemical structures to avoid overall bonemarrowtoxicity as, for the same project, every series may have its own hematotoxicityspecificity not acceptable for progressing those compounds. A choice has often tobe made in the function of therapeutic indication, usually in collaboration withclinicians, where perhaps a mild erythropenia might be more tolerable thanneutropenia. Equally interesting is the possibility of having series that do not displayhematotoxicity but which are toxic in the nonhematopoietic general toxicity cell line(HepG2). One can assume that this is the ideal case and thereforemove forward suchchemicals. However, this might be an indication of a possible hepatotoxicity issue,although HepG2s are poor predictors of liver toxicity.

Figure 17.5 Tier 1 erythroid assay qualifica-tion using compounds of similar chemicalpharmacology and structure. Fifteen com-pounds from a single pharmacological classwere evaluated in the tier 1 erythroid assayand in vivo measuring absolute number of

peripheral blood reticulocytes. r 2¼ 0.83.Tier 1 erythroid IC50 values are the averagefrom triplicate wells (n¼ 1 experiment);reticulocyte counts were based on resultsfrom an Advia hematology analyzer (n¼ 1).


The specificity (rate of false positives) and the sensitivity (rate of false negatives) aredifficult to calculate with the limited number of chemicals that have been so far testedboth in this system and in vivo in animals and human. False negatives, though, aremore acceptable than false positives at early stages of drug discovery. Indeed, falsenegatives would be spotted during regular GLP in vivo animal studies and would notreach the human population more than they currently do. However, false positivesmay lead to the rejection of a good chemical series that could have ended up as auseful drug for patients.Hence, increasing the level of confidence of the tier 1 assay isessential, which is in part the role of the tier 2 assay.

17.3.2Tier 2 Tests

Despite displaying a fair predictive value, the tier 1 assay is based on simplecytotoxicity measurement of cell lines, not primary cells, which may have lost anumber of primitive characteristics. Therefore, the trust level of this assay to embracea wide range of predictable events is not as high as it is for the CFU assay. It is thenadvisable to confirm some key findings of the tier 1 stage, by themore elaborated andmore validated CFU assay [43–49].The 35mm dish assay most frequently used was for the myeloid lineage (CFU-

GM), but there are also assays for erythroid (CFU-E/BFU-E), lymphoid (CFU-L),stromal (CFU-F) and megakaryocyte (CFU-Meg) lineages. All of these assays areavailable to evaluate human bone marrow and several of these assays are alsoavailable for evaluating toxicity in mouse, rat, dog [50] and monkey in order todetermine species-specificity. Hence, this is extremely useful to determine whether apositive result in tier 1 on mouse cell lines also holds in other species of higherinterest, like man. Our recommendation is to check some of the worst toxicants asdetermined in tier 1 in the CFU assays, to confirm the results and to gradually buildup the confidence into the predictivity of the tier 1 cell line assay. If this does indeedcorroborate the tier 1 assessment, the development of chemical series or chemicalswithin a series can be stopped and the chemistry refined following the structures ofthe less-toxic compounds (Figure 17.6). Equally some of the best compounds(nonhematotoxic) in tier 1 should be controlled in the CFU assay for confirmationof their innocuousness in the species of interest (Figure 17.6 – �Spot-check�). Suchcompounds would be the leading structures for even further refinement, if needed.It is relatively obvious that CFU assays cannot be used for wide profiling and that a

careful choice of some of the compounds tested in tier 1 should be tested on tier 2.Therefore, a constant exchange of data and information between the profiler and thechemist is essential.The 35mmdish assay detects compounds that are cytotoxic to or alter proliferation

of themultipotent stem cells, but themain limitation of the 35mmdish CFUassay isthe need to microscopically identify and count the colonies to determine the com-pound concentration that decreased the number of colonies by 50% (IC50) or 90%(IC90). The European Community for Validation of Alternative Methods (ECVAM)supported the recommendation of using the mouse and human CFU-GM IC90 with


the concentration that induced neutropenia in vivo in the mouse to calculate theexpected human maximum tolerated dose (MTD), in respect to bone marrow ADR(Figure 17.7) [45, 46]. However, the assay used in these studies is labor-intensive, low-throughput and requires highly trained staff. Several manuscripts have been pub-lished attempting to increase the throughput of these assays. For example, analgorithm was written to automatically count CFU-GM colonies [51]. This decreasedsubjectivity of colony counting increases reproducibility and generates a permanentrecordof the colonies, but the35mmdishassays still need tobe scanned,which takes asignificant amount of time.Malerba et al. [52]modified the assay into a 96-well format,but still required microscopic identification and counting of the colonies. The largestimprovement was the development of multiwell CFU assays [53] where the relativenumber of colonies was quantified using luminescence. This automatable formatgreatly increases the possibility of checking tier 1 results in tier 2, as the throughput ismuch higher than with 35mm dishes. If the cost of such an assay decreased enough,then it could possibly replace the tier 1 cell line assay. One possibility is to build up ahomemade platform, as the current authors did; however, the main limitation stillremains the cost and availability of the cytokines necessary for the differentiation andgrowth of the different lineages.

Figure 17.6 Hematotoxicity screening cascade. Assays usedduring drug discovery with tier 1 as the early discovery front-loading assay.


The �homemade assay,� modified from Horowitz et al. [54], is a semiautomated96-well assay with 50mL of primary bone marrow cells in methylcellulosecontaining cytokines and 50mL of compound titrated in DMSO and diluted inmedia(0.1% DMSO final concentration). Relative cell number was analyzed using 100mLof CellTiter Glo at the end of the culture period, one week for mouse andtwo weeks for human. At least 40 compounds could be evaluated in any givenexperiment using robotics to titrate and dilute compounds and then to add thediluted compounds to replicate plates that contain the tier 1 cells. The 96-wellsemiautomated mouse CFU-GM assay was qualified by comparing to the standard35mm dish CFU-GM assay using compounds with diverse structure and targets(Figure 17.8; r2¼ 0.77).The other limitation of the CFU assay in either format is that it remains an in vitro

environment where distant interactions, like livermetabolism (either detoxifying thecompounds or producing toxic metabolites) or immunomodulation, are absent.Investigating the mechanism of toxicity in animals for some carefully chosencompounds after being characterized in the two previous assays, can providevaluable information for the whole series, allow further refinement of the in vitroassays (e.g., addition of S9 for metabolism) and give an early indication of whichbiomarkers could be used in later GLP studies.

17.3.3Tier 3 Tests

Tier 3 is the evaluation of bone marrow after in vivo exposure to determine in vivoapplicability of the in vitro results (tiers 1 and 2) and predict clinical target- andchemistry-related toxicities. Historically, the bone marrow toxicity potential ofcompounds was evaluated by microscopic assessment of rat bone marrowcellularity from decalcified sternum bone slides, hematology and in some casesbone marrow differentials [55] only when a compound reached development.

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Figure 17.7 Predicted versus observed humanin vivoMTD using colony forming unit (CFU)assay.ThemouseCFU-GMIC50,humanCFU-GMIC50 andmousemaximum tolerated dose (MTD)were used to calculate predicted human MTD

basedontheEuropeanCommunity forValidationof Alternative Methods (ECVAM). The dataplotted are based on published results [45, 46].The linear regression line is plotted showing thecorrelation between the two assays.


Decrease in hematology parameters requires careful evaluation as it can result fromdrug-induced hematotoxicity or from increased cell loss. For example, microvascularhemorrhage from the gastrointenstinal tract results in decreased peripheral redblood cell numbers due to blood loss, even though the bone marrow is functioningadequately. There are a few limitations with bone marrow differentials that requirehighly trained clinical pathologists to do 200 or more cell differentials, but moreimportantly the differential only yields a percentage of cells without respect tothe absolute cell number. This can lead to misinterpretation of the results. Forexample, decreased percentage of a cell typewith an elevated absolute number of totalcells could yield a normal absolute cell number. To circumvent this limitation, a flowcytometric method was developed that reported the absolute numbers of lymphoid,immature myeloid, maturing myeloid, immature erythroid and maturing nucleatederythroid cells in rat, dog andmonkey bonemarrow [56]. This assay can screen the invivo bone marrow hematotoxicity potential of compounds, but slides for cytologywere always prepared in case a compound interfered with staining. The advantage ofthis and other flow cytometric methods developed [57, 58] include: (i) differentialbased on at least 10 000 cells; (ii) reporting absolute cell numbers; (iii) results reportedwithin a few days (compared to weeks for doing 200 cell microscopic differentials);(iv) bone marrow toxicity irrespective of the general pathophysiological pathway:proliferation, maturation and/or stromal cell interactions. Compounds inhibitingproliferation decrease the number of immature myeloid or erythroid cells.Compounds that inhibit maturation are detected by decreased maturing cells andaltered hematology. Stromal cell interactions are not directly evaluated by this assaybut stromal cells support hematopoiesis and so inhibition of stromal cell function or

Figure 17.8 Mouse 35mm dish versus mouse96-well colony-forming unit granulocyte/macrophage (CFU-GM) assays. Each compoundwas evaluated in the 96-well CFU-GM assay,12-point titration curve with triplicate samples

while the 35mm dish results were based onliterature results or a twelve point titrationcurve with duplicate 35mm dish results. Thelinear regression line is plotted showing thecorrelation between the two assays.


stromal cell loss results in decreased proliferation and/or maturation of the hemato-poietic cells.The tier 3 assay used was modified from Saad et al. [59]. This flow cytometric

method distinguishes between nucleated and nonnucleated cells, based on sidescatter and LDS-751 staining. LDS-751 is a nucleic acid stain (Figure 17.9). On ourflow cytometer, bone marrow reticulocytes (polychromatic erythrocytes) were withinthe LDS-751 positive population, as was demonstrated when evaluating isolatednonnucleated cells by sepharose column (Figure 17.10). Therefore a slightlymodifiedgating strategy for data analysis was used to quantify nonnucleated cells, reticulocytesand nucleated erythroid cells separately, in addition to the myeloid and lymphoidpopulations (Figure 17.11).

17.4Triggers for Hematotoxicity Testing

There is a high prevalence of bone marrow toxicity with antiproliferative oncologycompounds that also occurswithmanynon-antiproliferative compound classes but at amuch lower prevalence. It is these non-antiproliferative compounds that are of greatest

Figure 17.9 Rat in vivo hematotoxicity evaluatedusing flow cytometry (based on Saad et al. [59]).Gating strategy of flow cytometry evaluated ratbone marrow samples. N¼ at least 10 000 cells.Results include absolute number nucleated cells,myeloid cells, nucleated erythroid cells andlymphoid cells.


importance to evaluate early in drug discovery to influence chemistry, but it is typicallynot possible to evaluate all of these compounds within the company library or com-pounds generated by the chemists. Hence, three possible approaches are attempted.The first consists of selecting a handful of representative compounds which cover

the chemical space of a series and testing only those. If there are some alerts, thenfurther compounds can be tested. This can be done systematically for all series of allprojects. However, this absorbs a fair amount of resources for a potentially limitedreturn on investment.The second approach necessitates a mechanism to identify compounds or chemi-

cal series from a project that enter the screening cascade. These triggersmay includetarget-related information, previous experience and in silico analysis of compounds.One of the roles of a toxicologist involved in early discovery as a project team

representative can be to generate a list of potential and likely toxicities deduced fromtarget-related information such as tissue expression, similarity to other targets,precedent described in literature and sometimes chemical structure similarity.When

Figure 17.10 Flow cytometric method doesnot differentiate between nucleated erythroidcells and reticulocytes, on some instruments.Non-nucleated erythroid cells were isolatedusing cellulose fractionation. Part of thesample was stained with Wright-Giemsa andreticulocytes and mature nucleated cellsquantified by trained medical technologists.

Rest of the sample was stained using themethodby Saad et al. [59]. There are two non-nucleatederythroid populations based on LDS751 staining(LDS751� and LDS751dim). Additional stains(results not shown) indicate the LDS751dim cellsare reticulocytes and the LDS751� cells aremature non-nucleated erythrocytes.

17.4 Triggers for Hematotoxicity Testing j431

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reasonable theoretical concerns can be formulated, then project compounds need tobe evaluated using the proposed cascade, to assess the reality of those potential BMtoxicities. Furthermore, it is sometimes possible to determine whether bonemarrowtoxicity is due to pharmacology and/or formulate a structure–activity relationship.By using this targeted approach, one can limit compound-profiling activities to areasof high likelihood of BMT and optimize the cost-effectiveness of such screening.However, when hematotoxicity are observed in vivo for initial lead compounds or

projects, then backups or next generation projects have an easy trigger to justify athorough profiling of follow-up compounds through the whole cascade very early indiscovery.The third potential trigger of the cascade is in silico that can evaluate thousands of

compounds generated by the chemists for all projects, but the authors are not awareof any such in silico models at this time. However, some models are under develop-ment and should be implemented within the next couple years as more compoundsare evaluated using this BMTprofiling cascade. Five different bone marrow toxicityin silicomodels are needed as some compounds are toxic to only some of the lineages(myeloid, erythroid, lymphoid, megakaryocyte/platelet, stromal) while other com-pounds are toxic to allfive lineages. It is hoped that a thorough and constant use of thedescribed assays could feed the training sets of such in silico systems for betterprediction. Hence, with time, more and more triggers are likely to be due to in silicowarnings.

17.5Conclusions

Hematotoxicity is an ADR with varying incidence clinically and consists of drug-induced agranulocytosis/neutropenia, thrombocytopenia and anemia. There are atleast several mechanisms of drug-induced hematotoxicity still unknown for mostcompounds. A cascade of assays was developed and qualified to permit evaluation ofvarious compounds from a pharmacological target and similar chemical structures.The tier 1 assay is medium-throughput and allows a fast screening of small amountsof compounds early in drug discovery. Tier 2 assays are lower-throughput, but enablethe assessment of species-specificity and should be used to check tier 1 results. Thetier 3 assay evaluates the hematotoxicity potential of compounds by flow cytometryafter in vivo dosing. This cascade is used successfully, but still needs furtherqualification using non-antiproliferative compounds and verifying the ability of thecascade to predict clinical BMT ADR.

References

1 Vangala, S. and Tonelli, A. (2007)Biomarkers, metabonomics, and drugdevelopment: can inborn errors of

metabolism help in understandingdrug toxicity? AAPS Journal, 9,E284–E297.

References j433

2 Kola, I. and Landis, J. (2004) Can thepharmaceutical industry reduce attritionrates? Nature Reviews. Drug Discovery, 3,711–715.

3 Fung, M., Thornton, A., Mybeck, K.,Wu, J.H., Kornbuckle, K. and Muniz, E.(2001) Evaluation of characteristics ofsafety withdrawal of prescription drugsfromworldwide pharmaceutical markets –1960 to 1999.Drug Information Journal, 35,293–317.

4 Lubran, M.M. (1959) Hematologic sideeffects of drugs. Annals of Clinical andLaboratory Science, 19, 114–121.

5 Zhu, H., Li, Y. and Trush, M.A. (1995)Characterizatoin of benzo[a]pyrenequinine-induced toxicity to primarycultured bone marrow stromal cellsfrom DBA/2 mice: potential roleof mitochondrial dysfunction. Toxicologyand Applied Pharmacology, 130, 108–120.

6 McKee, E.E., Furguson, M., Bentley, A.T.and Marks, T.A. (2006) Inhibition ofmammalian mitochondrial proteinsynthesis by oxazolidinones. AntimicrobAgents Chemotherapy, 50, 2042–2049.

7 Chitnis, S., Mondal, D. and Agrawal, K.C.(2002) Zifovudine (AZT) treatmentsuppresses granulocyte-monocyte colonystimulating factor receptor type alpha(GM-CSFRa) gene expression in murinebone marrow cells. Life Sciences, 71,967–978.

8 Siraki, A.G., Deterding, L.J., Bonini, M.G.,Jian, J., Ehrenshaft, M., Tomer, K.B. andMason, R.P. (2008) Procainamide, but notN-Acetylprocainamide, induces proteinfree radical formation onmyeloperoxidase:a potential mechanism of agranulocytosis.Chemical Research in Toxicology, 21,1143–1153.

9 Pereira, A. and Dean, B. (2006) Clozapinebioactivation induces dose-dependent,drug-specific toxicity of human bonemarrow stromal cells: a potential in vitrosystem for the study of agranulocytosis.Biochemical Pharmacology, 72, 783–793.

10 Gray, M.W., Cedergren, R., Abel, Y. andSankoff, D. (1989) On the evolutionary

origin of the plan mitochondrion and itsgenome. Proceedings of the NationalAcademy of Sciences of the United States ofAmerica, 86, 2267–2271.

11 Riesbeck, K., Bredberg, A. and Forsgren,A. (1990) Ciprofloxacin does not inhibitmitochondrial functions but otherantibiotics do. Antimic Agents Chemther,34, 167–169.

12 Kroon, A.M., Donje, B.H.,Holtrop,M. andVan Den Bogert, C. (1984) Themitochondrial genetic system as a targetfor chemotherapy: tetracyclines ascytostatics. Cancer Letters, 24, 33–40.

13 Scatena, R., Bottoni, P., Botta, G.,Martorana, G.E. and Giardina, B. (2007)The role of mitochondria in pharma-cotoxicology: a reevaluation of an old,newly emerging topic. AmericanJournal of Physiology. Cell Physiology, 293,C12–C21.

14 Lavin, A.L., Hahn, D.J. andGasiewicz, T.A.(1998) Expression of functional aromatichydrocarbon receptor and aromatichydrocarbon nuclear translocator proteinsin murine bone marrow stromal cells.Archives of Biochemistry and Biophysics, 352,9–18.

15 vanGrevenynghe, J., Bernard,M., langouet,S.,LeBerre,C., Fest, T. andFardel,O. (2005)HumanCD34-positive hematopoietic stemcells constitute targets for carcinogenicpolycyclic aromatic hydrocarbons. TheJournal of Pharmacology and ExperimentalTherapeutics, 314, 693–702.

16 Pendurthi, U.R., Okino, S.T. and Tukey,R.H. (1993) Accumulation of the nucleardioxin (Ah) receptor and transcriptionalactivation of the mouse cyp1a-1 andcyp1a-2 genes. Archives of Biochemistry andBiophysics, 306, 65–69.

17 Yoon, B.I., Hirabayashi, Y., Kaneko, T.,Kodama, Y., Kano, J., Yodoi, J., Kim, D.Y.and Inoue, T. (2001) Transgene expressionof thioredoxin (TRX-ADF) protects against2,3,7,8-tetrachlorodibenzo-p-dioxin(TCDD)-induced hematotoxicity. Archivesof Environmental Contamination andToxicology, 41, 232–236.


18 Yoon, B.I., Hirabayashi, Y., Kawasaki, Y.,Kodama, Y., Kaneko, T., Kanno, J.,Kim, D.Y., Fujii-Kuriyama, Y. andInoue, T. (2002) Aryl hydrocarbonreceptor mediates benzene-inducedhematotoxicity. Toxicological Sciences, 70,150–156.

19 Galvan, N., Teske, D.E., Zhou, G.,Moorthy, B., MacWilliams, P.S.,Czuprynski, C.J. and Jefcoate, C.R. (2005)Induction of CYP1A1 and CYP1B1 in liverand lung by benzo(a)pyrene and7,12dimthylbenz(a)anthracene do notaffect distribution of polycylic hydro-carbons to target tissue: role of AhR andCYP1B1 in bone cytotoxicity. Toxicologyand Applied Pharmacology, 202, 244–257.

20 Garndner, I., Zahid, N., MacCrimmon, D.and Uetrecht, J.P. (1998) A comparisonof the oxidation of clozapine and olanza-pine to reactive metabolites and the toxicitythese metabolites to human leukocytes.Molecular Pharmacology, 53, 991–998.

21 Pisciotta, A.V., Konings, S.A., Ciesemier,L.L., Cronkite, C.E. and Lieberman, J.A.(1992) On the possible and predictabilityof clozapine-induced agranulocytosis.Drug Safety, 7 (suppl 1), 33–44.

22 Galati, G., Tafazoli, S., Sabzevari, O.,Chan, T.S. and O�Brien, P.J. (2002)Idiosyncratic NSAID drug inducedoxidative stress. Chemico-BiologicalInteractions, 142, 25–41.

23 Pereira, A., McLaren, A., Bell, W.R.,Copolov, D. and Dean, B. (2003) Potentialclozapine target sites on peripheralhematopoietic cells and stromal cells of thebone marrow. The PharmacogenomicsJournal, 3, 227–234.

24 Broome, C.S., Whetton, A.D. and Miyan,J.A. (2000) Neuropeptide control of bonemarrowneutrophil production ismediatedby both direct and indirect effects onCFU-GM. British Journal of Haematology,108, 140–150.

25 Liu, C., Ma, X., Jiang, X., Wilson, S.J.,Hofstra, C.L., Blevitt, J., Byati, J., Li, X.,Chai, W., Carruthers, N. and Lovenbert,T.W. (2001) Cloning and pharmacological

characterization of a fourth histaminereceptor (H(4)) expressed in bonemarrow.Molecular Pharmacology, 59, 420–426.

26 Corbel, S., Schneider, E. and Lemoine, F.(1995) Dy, Murine hematopoieticprogenitors are capable of both histaminesynthesis and update. Blood, 86, 531–539.

27 Gogu, S.R., Malter, J.S. and Agrawal, K.C.(1992)Zidovudine-inducedblockadeof theexpression and function of theerythropoietin receptor. BiochemicalPharmacology, 44, 1009–1012.

28 Wadelius, M., Stjernberg, E., Wiholm, B.E.and Rane, A. (2000) Polymorphisms ofNAT2 in relation to sulphasalazine-inducedagranulocytosis. Pharmacogenetics, 10,35–41.

29 Sebbag, L., Boucher, P., Davelu, P.,Boissonnat, P., Champsaur, G., Ninet, J.,Dureau, G., obadia, J.F., Vallon, J.J. andDelaye, J. (2000) Thiopurine s-methyl-transferase gene polymorphism ispredictive of azathioprine-inducedmyelosuppression in heart transplantrecipients. Transplantation, 69, 1524–1527.

30 Schwab, M., Schaffeler, E., Marx, C.,Fischer, C., Lang, T., Behrens, C., Gregor,M., Eichelbaum, M., Zanger, U.U. andKaskas, B.A. (2002) Azathioprine therapyand adverse drug reactions in patientswith inflammatory bowel disease: impactof thiopurine s-methyltransferasepolymorphism. Pharmacogenetics, 12,429–438.

31 Mosyagin, I., Dettling, M., Roots, I.,Mueller-Oerlinghausen, B. andCascorbi, I. (2004) Impact ofmyeloperoxidase and NADPH-oxidasepolymorphisms in drug-inducedagranulocytosis. Journal of ClinicalPsychopharmacology, 24, 613–617.

32 Kiyotani, K., Mushiroda, T., Kubo, M.,Zembutsu, H., Sugiyama, Y. andNakamura, Y. (2008) Association of geneticpolymorphisms in SLCO1B3 and ABCC2with docataxel –induced leucopenia.Cancer Science, 99, 967–972.

33 Biason, P., Basier, S. and Toffoli, G. (2008)UGT1A1�28 and other UGT1A

References j435

polymorphisms as determinants ofirinotecan toxicity. Journal ofChemotherapy, 20, 158–165.

34 Rha, S.Y., Jeung, H.C., Choi, Y.H., Yang,W.I., Yoo, J.H., Kim, B.S., Roh, J.K. andChung, H.C. (2007) An associationbetween RRM1 haplotype andgemcitabine-induced neutropenia in breastcancer patients. Oncologist, 12, 622–630.

35 Hor, S.Y., Lee, S.C., Wong, C.I., Lim, Y.W.,Lim, R.C., Wang, L.Z., Fan, L., Guo, J.Y.,Lee, H.S., Goh, B.C. and Tan, T. (2008)PXR, CAR, andHNF4alpha genotypes andtheir association with pharmacokineticsand pharmacodynamics of docetaxeland doxorubicin in asian patients. ThePharmacogenomics Journal, 8, 139–146.

36 Mealey, K.L., Fidel, J., Gay, J.M.,Imperllizeri, J.A., Clifford, C.A. andBergman, P.J. (2008) ABCB1-1Deltapolymorphism can predict hematologictoxicity in dogs treated with vincristine.Journal of Veterinary Internal Medicine/American College of Veterinary InternalMedicine, 22, 996–1000.

37 Mielke, S. (2007) Individualizedpharmacotherapy with paclitaxel.Current Opinion in Oncology, 19, 586–589.

38 Sandvliet, A.S., Huitema, A.D., Copalu,W., Yamada, Y., Tamura, T., Beijnen, J.H.and Schellens, J.H. (2007) Cyp2c9 andcyp2c19 polymorphic forms are related toincreased indisulam exposure and higher riskof severe hematologic toxicity.Clinical CancerResearch, 13, 2970–2976.

39 Sakamoto, K., Oka, M., Yoshino, S.,hazama, S., Abe, T., Okayama, N. andHinoda, Y. (2006) Relation betweencytokine promoter gene polymorphismand toxicity of 5-fluorouracil plus cisplatinchemotherapy. Oncology Reports, 16,381–387.

40 Brott,D.,Kelly,T.,Capobianchi,K.,Huggett,T., Goodman, J., Saad, A. and Pognan, F.(2007) Frontloading the evaluation of bonemarrow toxicity using a three-tiredapproach. The Toxicologist, 2007, 1169.

41 Huggett, T., Saad, A., Kelly, T., Pognan, F.,Otieno,M. and Brott, D. (2005) Validation

of an in vitro cell line for screeningmyelotoxicity. The Toxicologist, 2005,1626.

42 Hankins, W.D., Chin, K., Dons, R. andSigounas, G. (1989) Erythropoietin-dependent and erythropoietin-producingcell lines. Implications for research and forleukemia therapy. Annals of the New YorkAcademy of Sciences, 554, 21–28.

43 Erickson-Miller, C.L., May, R.D.,Tomaszewski, J., Osborn, B., Murphy,M.J., Page, J.G. and Parchment, R.E.(1997) Differential toxicity ofcamptothecin, otpotecan and 9-amino-camptothecin to human canine andmurine myeloid progenitors (CFU-GM)in vitro. Cancer Chemotherapy andPharmacology, 39, 467–474.

44 Pessina, A., Malerba, I. and Gribaldo, L.(2005) Hematotoxicity testing by cellclonogenic assay in drug development andpreclinical trials. Current PharmaceuticalDesign, 11, 1055–1065.

45 Pessina, A., Albella, B., Bueren, J.,Brantom,P., Casati, S.,Gribaldo, L.,Croera,C., Gagliardi, G., Foti, P., Parchment, R.,Parent-Massin, D., Sibiril, Y., Schoeters, G.and Van Den Heuvel, R. (2001)Prevalidation of a model for predictingacute neutropenia by colony forming unitgranulocyte/macrophage(CFU-GM) assay.Toxicol in Vitro, 15, 729–740.

46 Pessina, A., Albella, B., Bayo, M.,Bueren, J., Brantom, P., Casati, S.,Croera, C., Gagliardi, G., Foti, R.,Parchment, R., Parent-Massin, D.,Schoeters, G., Sibiril, Y., Van Den Heuvel,R. and Grialdo, L. (2003) Application of theCFU-GM assay to predict acute drug-induced neturopenia: an interanationalblind trial to validate a prediction model ofthe maximum tolerated dose (MTD) ofmyelosuppresive xenobiotics. ToxicolSciences, 75, 355–367.

47 Goldfain-Blanc, R., Wattrelos, O.,Casadevall, N., Beamonte, A., Delongeas,J.L. and Claude, N. (2004) Value of in vitromodels for the assessment of drug-inducedhaematotoxicity. Therapie, 59, 607–610.


48 Pessina, A., Croera, C., Bayo, M., Malerba,I., Passardi, L., Cavicchini, L., Neri, M.G.and Gribaldo, L. (2004) A methylcellulosemicroculture assay for the in vitroassessment of drug toxicity ongranulocyte/macrophage progenitors(CFU-GM). Alternatives to LaboratoryAnimals, 32, 17–23.

49 Parchment, R.E. (1998) Alternativetesting systems for evaluatingnoncarcinogenic, hematologic toxicity.Environmental Health Perspectives, 106(Suppl. 2), 541–547.

50 Deldar, A., Lewis, H., Bloom, J. andWeiss,L. (1988) Reproducibile cloning assays forin vitro growth of canine hematopoieticprogenitor cells and their potentialapplications in investigative hemato-toxicity. American Journal of VeterinaryResearch, 49, 1393–1401.

51 Crosta, G.F., Fumarola, L., Malerba, I. andGribaldo, L. (2007) Scoring CFU-GMcolonies in vitro by data fusion: a firstaccount.ExperimentalHematology,35, 1–12.

52 Malerba, I., Casati, S., Diodovich, C.,Parent-Massin, D. and Gribaldo, L. (2004)Inhibition of CFU-E/BFU-E and CFU-GMcolony growth by cyclophosphamide,5-fluorouracil and taxol: development ofhigh-throughput in vitromethod.Toxicol invitro, 18, 293–300.

53 Rich, I.N. and Hall, K.M. (2005)Validation and development of a predictiveparadigm for hematotoxicology usingmultifunctional bioluminescence colony-forming proliferation assay. ToxicolSciences, 87, 427–441.

54 Horowitz, D. and King, A.G. (2000)Colorimetric determination of inhibitionof hematopoietic progenitor cells in softagar. Journal of Immunological Methods,244, 49–58.

55 Bollinger,A.P. (2004)Cytological evaluationof bone marrow in rats: indications,methods and normal morphology.Veterinary Clinical Pathology, 33, 58–67.

56 Martin, R.A., Brott, D.A., Zandee, J.C. andMcKeel,M.J. (1992)Differential analysis ofanimal bone marrow by flow cytometry.Cytometry, 13, 638–643.

57 Criswell, K.A., Sulkanen, A.P.,Hochbaum,A.F. andBleavins,M.R. (2000)Effects of phenylhydrazine or phlebotomyon peripheral blood, bone marrow anderythropoietin in wistar rats. Journal ofApplied Toxicology, 20, 25–34.

58 Weiss, D.J. (2001) Use of monoclonalantibodies to refine flow cytometricdifferential cell counting of canine bonemarrow cells. American Journal ofVeterinary Research, 62, 1273–1278.

59 Saad, A., Palm, M., Widell, S. and Reiland,S. (2000) Differential analysis of rat bonemarrow by flow cytometry. ComparativeHaem International, 10, 97–101.

60 Garbe, E. (2007) Non-chemotherapy drug-induced agranulocytosis. Expert Opinionon Drug Safety, 6, 323–335.

61 Andres, E., Zimmer, J., Affenberger, S.,Federici, L., Alt, M. and Maloisel, F.(2006) Idiosyncratic drug-inducedagranulocytosis: update of an old disorder.European Journal of Internal Medicine, 17,529–535.

62 Flanagan, R.J. and Dunk, L. (2008)Haematological toxicity of drugs used inpsychiatry. Human Psychopharmacology-Clinical and Experimental, 23, 27–41.

63 Andres, E., Federici, L., Weitten, T., Vogel,T. and Alt, M. (2008) Recognition andmanagement of drug-induced bloodcytopenias: the example of drug-inducedacute neutropenia and agranulocytosis.Expert Opinion on Drug Safety, 7, 481–489.

References j437

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