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The NCI Approach To Drug Development Edward A. Sausville, M.D., Ph.D. Developmental Therapeutics Program National Cancer Institute.

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Presentation on theme: "The NCI Approach To Drug Development Edward A. Sausville, M.D., Ph.D. Developmental Therapeutics Program National Cancer Institute."— Presentation transcript:

1 The NCI Approach To Drug Development Edward A. Sausville, M.D., Ph.D. Developmental Therapeutics Program National Cancer Institute

2 Goals Of Preclinical Drug Studies Discovery of “lead structures” “Refinement”: chemistry, pharmacology, efficacy =“Early” development Late development: formulation, dose form, toxicology Scientific framework

3 Goals Of Preclinical Drug Studies IND = “Investigational New Drug” application = approval by FDA to conduct human studies; main criterion : SAFETY AND LIKELY REVERSIBLE TOXICITY = allows start of Phase I trials NDA = “New Drug Application” = basis for sale to public; main criteria: SAFETY AND SOME MEASURE OF EFFICACY = result of Phase II/III trials Regulatory framework

4 Cancer Drugs: How Do We Know We Have A Winner? - PHASE III CLINICAL TRIAL = WINNER - PHASE II = POTENTIAL WINNER R x ; Time? Treatment B or no R x Time % Alive Treatment A - PRECLINICAL MODEL (e.g., mouse or rat) Cytotoxic Tumor Size Time Untreated Cytostatic R x

5 Cancer Drugs: How To Pick A Winner? “VALIDATED” CANCER TARGETS DNA Alkylators Antimetabolites Topo I / II Tubulin Receptors Nuclear Cell Surface (Immune?) Oncogene Proteins (2001: AT LAST!)


7 Problems With Empirical Models Lack of predictive power in vivo Poor correlation of non-human with human pharmacology Divorced from biology Inefficient: many compounds screened; developed, but have “late” = clinical trials outcome at Phase III to define “validation” of compound action

8 KRN5500 H 3 C(CH 2 ) 8 CH=CHCH=CHCO 2 H DeacylationSAN-Gly Protein Synthesis

9 Effect Of KRN5500 On Colo-205 Athymic Mouse Xenografts Median Tumor Weight (mg) Day Posttumor Implantation 5000 4500 4000 3500 3000 2500 2000 1500 1000 500 0 8121518222629333641 vehicle 13.5 qdx5 33.5 q4dx3 22.4 q4dx3 20 qdx5 50 q4dx3 30 qdx5 + X

10 KRN5500 Plasma Concentrations On Effective Schedule(20 mg/kg/d) In Mice Plasma Concentration (  M) Time (days)

11 Summary Of KRN5500 Phase I 26 patients as IV once per day over 5 days Dose limiting toxicity = interstitial pneumonitis MTD = 2.9 mg/M 2 /d x 5 Achieve only 0.75 - 1  M at 3.7 mg/M 2 /d x 5 4/6 patients with >25% incr C max have grade 4 toxicity Data of J. P. Eder, DFCI

12 In Vivo i.e., Intact Animal Tumor Models The information received depends on the question asked: not all models are appropriate for all questions Drugs need different types of models at different times in their “discovery / development” life cycle “Pharmacology” models to qualify compound “Efficacy” models to define potential for biologic effect  Target driven  Target unselected “Biology” models to confirm ONLY the target or molecular events related to target are affected

13 In Vivo Activity vs Clinical Activity (39 Agents)


15 “Misfiring” or Abnormality of Cell Cycle Imbalance of Genes Regulating Cell Death Immortality / Telomerase Angiogenesis / Invasion Phenotype How To “Build” A Cancer Cell Cancer cells possess defined “families” of lesions with common outcomes G1G1 S G2G2 M G0G0 - “Oncogenes” turned on - “Suppressor genes” turned off - Mimic Growth Regulatory “Signal Transduction” Tumor Size Cell Death Cell Proliferation (After Varmus, Bishop, Weinberg, Croce, Folkman, Hanahan … etc.)

16 * Cytogenetics Breakpoints Molecules (bcr-abl) * “Positive” selection from tumor DNA Active oncogenes (signal transduction) * Tumor gene expression profiling (CGAP) * Binding partners (geldanamycin, rapamycin, fumagillin) * Computational algorithm (molecule target) * Cell metabolism / Cell cycle effects * Suggest single targets Inefficient * Libraries of molecules and precisely defined organisms Molecular Target Definition - How To? BIOLOGY: “ RETROFIT” ACTIVE MOLECULES: “CLASSICAL:” CHEMICAL GENETICS: - COMPARE - Cluster analysis

17 bcr-abl As Target: Rationale Apparently pathogenetic in t9:Q22 (Ph+) CML/ALL Absence in normal tissues Modulate signal transduction events downstream Maintenance of chronic phase Adjunct to bone marrow transplantation

18 bcr-abl Fusion Protein bcrSH2 VSH2/SH3kinaseNT DNAActin bcr autophosphorylation Phosphorylation of other substances McWhirter JR, EMBO 12:1533, 1993

19 Example Of “Rational” Approach: bcr-abl directed agents erbstatinlavendustinpiceatannol AG957AG1112 CGP 57148B = STI571 Natural product empiric lead 1st generation synthetic 2nd generation synthetic; in clinic

20 STI571: An Oral In Vivo Bcr-abl Kinase Inhibitor Tyr phosphorylation in vivo le Coutre et al, JNCI 91:163, 1999 Antitumor activity in vivo (hrs) (days)

21 NEJM 344: 1031, 2001 Efficacy And Safety Of A Specific Inhibitor Of The Bcr-abl Tyrosine Kinase In Chronic Myeloid Leukemia BRIAN J.DRUKER,M.D.,MOSHE TALPAZ,M.D.,DEBRA J.RESTA,R.N.,BIN PENG,PH.D., ELISABETH BUCHDUNGER,PH.D.,JOHN M.FORD,M.D.,NICHOLAS B.LYDON,PH.D.,HAGOP KANTARJIAN,M.D., RENAUD CAPDEVILLE,M.D.,SAYURI OHNO-JONES,B.S.,AND CHARLES L.SAWYERS,M.D. % in Metaphase 0100200300400 100 80 60 40 20 0 Ph Chromosome + Cells White Cell Count (cells x 10 -3 / mm 3 ) 0306090120 150 100 10 1 Duration of Treatment with STI571 (Days)

22 NCI Drug Discovery Aids to find targets / link targets with drugs -Cancer Genome Anatomy Project (CGAP) -Developmental Therapeutics Program In Vitro Drug Screen Where the target is known: build its assessment into the selection and development of a compound: e.g., 17-allylamino 17-demethoxy geldanamycin (17-AAG) Where the target is unknown, define it or a proximal indicator of effect in parallel with conventional development path: e.g., UCN-01 protein kinase inhibitor A Marriage Of Empirical And Rational Opportunities

23 Cancer Genome Anatomy Project: PROCESS Tumor material (archival) “Laser capture microdissection” of tumor cells Creation of tumor-derived cDNA libraries Sequence to establish uniqueness Deposit in public domain from defined sections

24 Establishing for a cell the repertoire of genes expressed, together with the amount of gene products produced for each, yields a powerful "fingerprint". Comparing the fingerprints of a normal versus a cancer cell will highlight genes that by their suspicious absence or presence (such as Gene H ) deserve further scientific scrutiny to determine whether such suspects play a role in cancer, or can be exploited in a test for early detection. Normal Cell Cancer Cell Gene Expression: The Cell’s Fingerprint

25 NCI In Vitro Drug Screen 1985 Hypothesis: Emerging Realities: Cell type specific agents Activity in solid tumors Unique patterns of activity, cut across cell types Correlations of compound activity AND Cell type selective patterns found - relate to molecular “target” expression - generate hypothesis re: molecular target

26 All Cell Lines Log 10 of Sample Concentration (Molar) Percentage Growth 100 50 0 -50 -100 -9-8 -7 -6-5-4 National Cancer Institute Developmental Therapeutics Program Dose Response Curves NSC: 643248-Q/2 (a rapamycin)Exp. ID: 9503SC35-46

27 Pattern Recognition Algorithm: COMPARE Goal: COMPARE degree of similarity of a new compound to standard agents Calculate mean GI 50, TGI or LC 50 Display behavior of particular cell line as deflection from mean Calculate Pearson correlation coefficient: 1 = identity ; 0 = no correlation resistantmeansensitive

28 TaxolHalichondrin B Daunorubicin Topoisomerase II Leukemia NSCLC Small Cell Lung Colon CNS Melanoma Ovarian Renal Agents With Similar Mechanisms Have Similar Mean Graphs Tubulin

29 Drug Target Clusterings Reveal Clues To Mechanism Nature Genetics 24: 236, 2000; 5FU/DPYD L-Asparaginase /ASNS

30 Geldanamycin 17-AAG 122750 330507 OMe NHCH 2 CH=CH 2 RNSC Geldanamycin Structure carbamate ansa ring benzoquinone

31 Benzoquinoid Ansamycins Initial Cell Pharmacology Reduce levels or inhibit transformation by a large number of PTKs: src, yes, fps, erbB1, lck e.g., 17AAG decrease erbB2 under conditions where overall transcription/translation little affected (Miller et al, Cancer Res 54: 2724, 1994) Effect of 6 hr, 0.35  M herbimycin A on SKBr3 cells p185 protein p185 Y-P erbB2 RNA Prot syn RNA syn ATP ATP/ADP 35 5 130 84 90 99 108 Parameter % of control 02468 150 100 50 0 MDA MB 453 % Control p185 Protein p185 PY Hours

32 DTP, NCI In Vivo Evaluation Of Geldanamycin In PC3 Prostate CA # 20 6 Dose (mg/kg) 0 3.4 2.3 1.5 Route of administration – i.p. Schedule qd x 5 (9) Drug Deaths 03100310 % Opt T/C (D) --- Toxic 33(22) 90(15) Growth Delay --- 50 3 Conclude: Narrow therapeutic index on this schedule Solubility of agent major problem for other schedules Early Stage, Athymic Mouse Xenograft

33 18 Atom Spacer Bead Geldanamycin Bead

34 Geldanamycin Beads Identify Hsp90 As Binding Partner Neckers et al, PNAS 91:8324, 1994 1234 p90 R. Lysate 1) Bead-Geld 2) Bead-Geld + Geld 3) Bead-Geld + Geldampicin 4) Bead

35 C. ER PR etc Cyclin D Hsp 90 pAKT EIF2  kinase raf erbB2 EGFR lck, met, etc G0G0 telomerase B. nucleus * hsp 90 * hsp 90 * hsp 90 A. X degradation nucleus X hsp 90 Immature X Mature X ER folding X -mRNA X Hsp 90

36 Three Dimensional View Of Geldanamycin Binding Pocket In Amino Terminus Of Hsp90 Stebbins et al, Cell 89:239, 1997

37 17-AAG Binds To Hsp90 & Shares Important Biologic Activities With Geldanamycin dose (nM) erbB2 (% of base line) Raf-1 (% of base line) Schulte & Neckers, Cancer Chemother Pharmacol 42: 273, 1998 120 100 80 60 40 20 0 0110100100010000 17-AAG GA 120 100 80 60 40 20 0 0110100100010000 17-AAG GA dose (nM) p185 erbB2 17-AAGGA (  M) 0.03 0.1 0.3 0.5 2 0.03 0.1 0.3 0.5 2 control Raf-1 17-AAGGA (  M) 0.03 0.1 0.3 0.5 2 0.03 0.1 0.3 0.5 2 control

38 UCN-01 Potent antiproliferative agent Cell cycle arrest DNA-damage G2 checkpoint abrogation 37nM 300-600 nM ~50nM IC 50 (DTP screen)

39 A DNA Damage G2 Checkpoint Is Mediated By CDKs: UCN-01 Action spRad3(hATM/hATR) Chk1-P Chk1 14-3-3 Cdc25-P(Ser 216 )Cdc25-P(Ser 216 )-14-3-3 Cdc2 ActiveActive? Active Inactive G 2 arrest Enter mitosis Cdc25 Cdc2-P(Tyr 15 ) Adapted from Weinert, Science 277:1450, 1997 UCN-01 Chk 1 mediates the G2 checkpoint

40 UCN-01 Infusional Phase I Trial G2 Checkpoint Abrogation % G2 checkpoint abrogation 70 60 50 40 30 20 10 0 0101000100000 nM UCN-01 70 60 50 40 30 20 10 0 30405060 UCN-01 (mg/m 2 /day) UCN-01 w/o plasma UCN-01 in plasma

41 Challenges In Pursuing The Molecular Therapeutics Of Cancer Must change thinking from histologic to molecular diagnoses (CGAP, array technology) Develop new means (imaging, probes) to assess molecular pharmacodynamics Must move away from cytotoxicity as sole primary endpoint: assess and evaluate cytostatic effect Promote patient participation in clinical trials Develop speed and efficiency in answering critical clinical questions

42 Goals For Cancer Drug Screening In The New Millennium Associate novel chemotypes with defined targets may utilize purified targets at the “front end” may define targets in pathway/organisms may “retrofit” molecules to targets or pathways by statistical approaches Allows facile tools for chemical/pharmacological optimization Define targets of relevance to and translatable in early clinical trials

43 Summary: Developmental Therapeutics Program, NCI Novel agents directed at molecular targets important to cancer pathogenesis and progression Interdisciplinary collaborators: academia, industry, intramural NCI Contribute agents and regimens for use by intra / extramural investigators

44 Acknowledgements NCI V. Narayanan, R. Schultz J. Johnson, S. O’Barr M. Hollingshead, S. Stinson L. Rubinstein A.Monks, N. Scudiero K. Paull, D. Zaharevitz, S. Bates S. Holbeck, J. Weinstein A. Senderowicz A. Murgo, S. Arbuck G. Kaur, P. Worland, Q. Wang P. O’Connor L. Neckers, L. Whitesell D. Newman H. Piwnica-Worms Wash U V. Pollack Pfizer M. Roberge U. Brit. Columbia

45 Our next speaker is: Ms. Shannon Decker Office of the Associate Director Developmental Therapeutics Program

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