Michelle Quinlan, PhD Associate Director of Biostatistics

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Presentation transcript:

Insights from former UNL graduate student to current Biostatistician at Novartis Oncology Michelle Quinlan, PhD Associate Director of Biostatistics Novartis Oncology, East Hanover, NJ

Outline Background Life as a Biostatistician at Novartis Oncology Clinical Pharmacology (CP) Biostats at Novartis Oncology General advice for graduate students UNL experiences which were helpful Questions?

Background 2005: BA from Concordia University (major Math/Business, minor Actuarial Science) 2007: MS in Statistics from UNL 2010: PhD in Statistics from UNL (dissertation on shelf life estimation) 2010-present: Clinical Pharmacology Biostatistician at Novartis Oncology

Life as a Biostatistician at Novartis Oncology

Novartis Oncology Global headquarters: Basel, Switzerland Background Global headquarters: Basel, Switzerland US headquarters: East Hanover, NJ Other locations Hyderabad, India Paris, France Tokyo, Japan Impacting cancer patients one drug at a time

Role of biostatistician at Novartis Oncology Member of clinical trial team Responsibilities as member of cross functional clinical trial team include: Providing input to clinical trial protocols & case report forms (data collection) Creating statistical analysis plans Working with programmers to create outputs for clinical study report (CSR) Writing statistical results in CSR Life as a Biostatistician

Role of biostatistician at Novartis Oncology Member of submission team Responsibilities as member of team preparing documentation for submission to health authorities (HA) include: Creating statistical analysis plans to address clinical pharmacology, safety, and efficacy aspects of drug Preparing datasets for submission to FDA Answering ad hoc HA questions

Role of biostatistician at Novartis Oncology Member of exposure-response team Responsibilities as member of exposure-response team to establish correct dose for further development: Working with clinical pharmacologists and clinicians to utilize data to make inference on recommended dose Addressing questions such as: Does increasing exposure increase probability of adverse events? Does increasing exposure increase efficacy? What is the optimal dose (maximum efficacy, minimum side effects)

Now a glimpse into Clinical Pharmacology (CP) Biostatistics at Novartis Oncology...

Intro to clinical pharmacology (CP) studies CP studies form basis of early drug development work & remain important component of late stage development Aims of CP studies include: To assess how much drug in the body at a given dose (at a given time) To determine dosing strategy (single/repeat dose, IV/oral) To link drug concentration to pharmacodynamics (efficacy and safety) Typically done in healthy volunteers if possible

Types of CP studies Examples Different objectives corresponding to different types of CP studies, e.g. ADME - Organ impairment (renal/hepatic) Bioequivalence - Thorough QT Bioavailability - Drug-drug interaction Food effect - Ethnic sensitivity  These studies are used to obtain information that will go onto drug label and package inserts

Bioequivalence studies Formally demonstrate two formulations have similar bioavailability e.g. rate (Cmax) and extent (AUC) of absorption are the same for Tablet vs. Capsule

Bioequivalence studies Statistical analysis involves computing geometric mean ratio and 90% CI for ratio of PK parameters from e.g. Tablet vs. Capsule and comparing results to 0.80- 1.25 bounds Six example scenarios, do they meet bioequlvalence criteria? Answers: 1, 2: yes 3: no (could have passed with >N) 4: failed (likely formulation effect, could have passed with >N) 5, 6: no (completely different)

Other CP studies Food effect Organ impariment Food effect, Organ impairment Food effect Statistical analysis involves computing geometric mean ratio and 90% CI of PK parameters from fed state (high fat or low fat meal) vs. fasted state Ratios <<1 or >>1 indicate negative or positive food effect Organ impariment Most drugs are eliminated either through renal or hepatic excretion; many are metabolized in liver and excreted renally Decreased clearance of drug by impaired liver/kidney Increased Cmax & likelihood of adverse events associated with exposure Potential dose reduction in patients with impaired hepatic/renal function

Other CP studies Drug-drug interaction Goals of DDI study Metabolic elimination can be inhibited, activated, or induced by concomitant drugs Investigational drug may inhibit/induce metabolism of other compounds Goals of DDI study Compare geometric mean ratio of PK parameters of drug with & without interacting drug Determine if interaction necessitates dose adjustment or contraindication on label

Helpful UNL experiences/courses General advice & Helpful UNL experiences/courses

General advice for graduate students Establish contacts with professors and people in areas you wish to work Pursue research/teaching assistantships to cover costs of school Seek out internships; first hand experience goes a long way Research potential jobs/areas of statistics online Masters is helpful but some industries (e.g. pharmaceutical) require PhD; PhD makes you more marketable The more you put into your education the more you will get out of it!

Helpful UNL experiences/courses Research assistantship with PQRI Stability Shelf Life Working Group; allowed interaction with members of pharma industry Attending conferences Working with classmates on challenging homework problems Weekly seminars Asking questions/getting clarification from professors on course material

Helpful UNL experiences/courses All courses were helpful; most relevant were: Generalized linear mixed models Clinical trials course through UNMC Experimental design (and theory) Categorical data analysis Courses I did not take but would have been helpful Survival analysis

Summary Exciting opportunities in Biostats at Novartis Oncology Work cross functionally to bring new treatments to cancer patients Use statistics to determine information on drug label related to safety and efficacy Make the most of your graduate school experience Seek out internships; first hand experience goes a long way Reach out to professors for advice and assistance Establish contacts in areas you wish to work

Questions?