Life Science Consulting Case Interview: Case Studies

Life science consulting case studies in interviews are pharma, biotech and MedTech strategy problems, such as a drug launch, a pipeline asset valuation or a payer access question, that add clinical evidence, regulatory timing and reimbursement to standard case logic. For a pharma or biotech prompt, follow the patient funnel from eligible population to diagnosed, treated, and accessible patients; for MedTech, add procedure volume, purchasing stakeholders, reimbursement, and adoption. A generic market-entry tree is useful only after you adapt it to those constraints.

What is a life science consulting case interview?

A life science consulting case interview is a live problem-solving exercise, typically 30 to 45 minutes, in which you structure and solve a pharma, biotech or MedTech business question out loud while the interviewer supplies data on request. Length and format vary by firm: some interviewers lead you through a fixed list of questions, others expect you to drive. Firms with life science practices, such as ZS, L.E.K., IQVIA and Huron, use these cases for specialist roles, and generalist firms may use an industry case for candidates who want healthcare work. Ask your recruiter for the format.

How do you solve a life science consulting case interview?

Work through six steps in order, and say each one out loud:

1. Clarify the goal. Repeat the decision in one sentence, then ask two or three questions about the disease, the product, competitors and payers (the lists are below).
2. Structure the problem. Start from four buckets, market, pricing, payer access and commercial model, and drop or add buckets to fit the prompt.
3. Open with the patient funnel. Take the eligible population down to diagnosed, treated and reachable patients before you apply share or price.
4. Run the math. Peak revenue is treated patients times share times net price. For an unapproved asset, weight the result by the chance each trial phase succeeds.
5. Test the risks that change the answer. Check clinical evidence, how payers will cover the product, competitor timing and loss of exclusivity.
6. Recommend in 30 seconds. Give the decision first, then two reasons with numbers, the main risk and the next step.

The solved case below walks through steps 3 to 6 with numbers.

What life sciences cases test

• Industry vocabulary matters: FDA phases, NDA/BLA, PBMs, HEOR, formulary tiers, rNPV, patent cliff, and LOE.
• The most reusable structure is market assessment, pricing strategy, payer access, and commercial model.
• ZS publishes extensively on commercial analytics and market access; the L.E.K. / LEK case interview guide is useful for strategy and diligence practice; Huron publishes healthcare-operations and commercialization work.
• Simon-Kucher's published work makes pricing and value communication relevant practice themes for many of its life-sciences roles.
• Generic consulting frameworks are only a starting point. Adapt them to payer, provider, patient, and regulator constraints before you recommend.

Life science consulting case study example: a solved pharma case with numbers

This is an original six-question life science consulting case study you can run alone in about 30 minutes. Every number is a case input, not market data. Work each question before reading the answer key.

Prompt: "Northbay Pharma has a new injectable biologic that works in two inflammatory diseases. It can only fund one Phase III program next year. Which indication should it pursue first?"

Exhibit 1: US patient funnel (case inputs)

Exhibit 2: Commercial inputs (case inputs)

Question 1: How many patients are on an advanced therapy in each indication? Answer: A = 1,000,000 x 60% x 30% x 50% = 90,000. B = 200,000 x 80% x 50% x 70% = 56,000. Indication A has five times the prevalence but less than twice the treated pool.

Question 2: What is peak revenue in each indication? Answer: A = 90,000 x 10% = 9,000 patients x $30,000 = $270M. B = 56,000 x 20% = 11,200 patients x $45,000 = $504M.

Question 3: Which indication should Northbay prioritize, on the numbers and beyond them? Answer: B. It has almost twice the peak revenue and a cheaper Phase III. Beyond the numbers, B has two competitors instead of nine, so the share assumption is easier to defend. The risk in B is the smaller pool: if the trial shows weaker data than expected, there is less room to recover share.

Question 4: How many years of peak sales does it take to repay the Phase III cost in each indication? Answer: Ignore ramp-up, discounting and trial risk for now. A = $270M x 40% = $108M of profit a year, so $250M / $108M = about 2.3 years. B = $504M x 40% = $201.6M a year, so $180M / $201.6M = about 0.9 years. B repays its trial cost in under a year of peak sales, A takes more than twice as long, and that gap supports choosing B. Then add the caveat: this is a best case, because a Phase III failure would leave the whole cost unrecovered.

Question 5: What payer access questions would you raise for Indication B? Answer: Will payers require patients to fail an existing therapy first (step therapy)? Which benefit covers an injectable here? What comparative data will payers need to justify a $45,000 net price against the two incumbents? In A, the main issue would instead be rebates, since biosimilars push net prices down across a crowded class.

Question 6: Give the recommendation in 30 seconds. Answer: "Fund Phase III in Indication B first. It offers about $504M peak revenue against $270M for A, costs $70M less to run, repays that cost in about 0.9 years of peak sales against 2.3 for A, and faces two competitors instead of nine. Before committing, confirm the share assumption with payer research on step therapy and pricing. Keep A as a follow-on indication once B's data is in."

To practice the operations side of a biopharma case with an interviewer, run the guided Biopharma Outsourcing to Mexico case.

Further practice: official employer cases

Two life sciences consulting firms publish their own practice cases. Use them after the case above, because they show each firm's own question style:

• ZS practice cases on ZS's careers site.
• Trinity Life Sciences practice case study on Trinity's own site.

What Makes Life Sciences Cases Unique

The patient, provider, and payer perspectives form a useful starting lens for many commercial life-sciences cases:

• Patient: Who has the disease? How are they diagnosed? Are they treatment-naive or pre-treated?
• Provider: Which physicians prescribe? What drives their prescribing decisions (efficacy data, safety profile, peer influence, KOL opinion)?
• Payer: Will insurance cover the product, under which benefit, at which site of care, and with what prior-authorization or utilization-management requirements?

Layered over this triangle are three additional constraints that standard consulting cases do not include:

1. FDA regulatory pathway: Is this a New Drug Application (NDA) for a small molecule or a Biologics License Application (BLA) for a biologic? What clinical evidence is required for approval? What label restrictions might limit the indicated population?
2. Patent and exclusivity timelines: When does the molecule lose market exclusivity? Is a biosimilar competitor likely within the commercial forecast window?
3. Health economics and outcomes evidence: Does the product's value proposition hold up to economic and outcomes analysis? What evidence will payers require for the relevant pharmacy- or medical-benefit coverage decision?

Use only the constraints relevant to the prompt. Omitting a material regulatory, exclusivity, or evidence constraint can make the recommendation incomplete.

Life sciences and healthcare practice cases at a glance

How a life sciences case works: it adds clinical evidence, regulatory timing, reimbursement and patient access to standard strategy logic, so adapt a generic tree before you use it.

Start free now: Biopharma Outsourcing to Mexico is a BCG-style operations case adapted from the Wharton casebook: a US maker of life-saving biomaterials, with manufacturing costs up since COVID, is weighing Mexico facilities. It has 7 questions, 1 with math, 1 exhibit, and a median of 22 minutes across 14 completed voice runs. An AI interviewer runs it out loud, shows each exhibit when you reach it and scores the debrief. Your first full case is free when you create an account.

Case (style, industry)	Quant difficulty	Qualitative difficulty	The math you run	Median time
Biopharma Outsourcing to Mexico (BCG, biomanufacturing). 7 (1 with math), 1 exhibit.biomanufacturingQuant difficulty easyQualitative difficulty medium22 min· 14 voice runsTry free	easy	medium	Variable cost per unit, annual savings	22 min14 voice runs22 min, 14 voice runs	Try free
Goodbye Horses (Independent, healthcare). 8 (4 with math), 2 exhibits.healthcareQuant difficulty mediumQualitative difficulty hardFewer than 10 runsTry free	medium	hard	Sale value, project NPV portfolio	Fewer than 10 runsFewer than 10 runs	Try free
MedSuite Technologies Hospital Software Pricing (McKinsey, hospital software). 8 (3 with math), 2 exhibits.hospital softwareQuant difficulty mediumQualitative difficulty medium20 min· 18 voice runsTry free	medium	medium	Revenue at each price point, tiered pricing	20 min18 voice runs20 min, 18 voice runs	Try free
HarborHealth Acquisition of MedLink Virtual Care (BCG, digital health). 8 (2 with math), 4 exhibits.digital healthQuant difficulty mediumQualitative difficulty hard27 min· 28 voice runsTry free	medium	hard	EV/EBITDA multiple, maximum justified offer	27 min28 voice runs27 min, 28 voice runs	Try free

Two are adapted from consulting club casebooks (Wharton and Duke Fuqua); the rest were written for Road to Offer. More are in the case library, 92 cases in all. Every debrief scores seven categories: structure (25% of the score), quantitative analysis (20%), business judgment (15%), and problem understanding, exhibit reading, communication and synthesis (10% each), with feedback on every question. Median times come from completed runs between June 25 and September 22, 2026, and count runs, not people.

Life sciences consulting interview questions

These six practice prompts are written for this guide to cover the common case types. They are practice material, not questions reported from any firm's interviews. Run each one with the six steps above and time yourself.

Before you answer any of them, ask the questions in the next list.

Clarifying questions for life sciences cases

Ask two or three of these before you structure, picking the group that matches the prompt.

About the disease

• How many people have it, and how many are diagnosed?
• Is it chronic or acute, and how severe is it for the patients in scope?
• How are patients treated today, and where does the current standard of care fall short?

About the product

• What stage is it in: preclinical, Phase I to III, filed, or approved?
• Is it a small molecule or a biologic, and how is it given (pill, injection, infusion)?
• What does the clinical data show against the standard of care on efficacy and safety?

About competitors

• Which products are approved or in late-stage trials for the same patients?
• When do the main competitors lose exclusivity, and are generics or biosimilars coming?

About payers

• Is the product covered under the pharmacy benefit or the medical benefit?
• What evidence will payers ask for, and do they already require step therapy or prior authorization in this class?

Which life science consulting case studies should you practice?

Practice five life science consulting case studies: drug launch strategy, portfolio and pipeline prioritization, market access and payer strategy, pharma or biotech M&A, and medical device market sizing. Treat them as practice archetypes, not a guaranteed firm question list.

1. Drug Launch Strategy

A useful archetype is a pharma company preparing or correcting a launch. One adaptable structure is market assessment, pricing, payer access, and commercial model.

Relevant published work: L.E.K., McKinsey, BCG, and Simon-Kucher all publish on launch, portfolio, commercial, or pricing questions; that does not prove a specific interview prompt.

2. Portfolio Prioritization and Pipeline Asset Allocation

A pharma or biotech company has multiple pipeline assets at various stages and limited R&D budget. Which assets should they fund? This requires risk-adjusted NPV (rNPV) modeling (applying stage-specific probability of success to projected cash flows before discounting) alongside strategic criteria like competitive differentiation and unmet need.

Relevant published work: Strategy firms publish on portfolio and R&D prioritization; use the job description to judge likely depth.

3. Market Access and Payer Strategy

A product has been approved but access is weak. First identify whether it is primarily covered through the pharmacy benefit, medical benefit, or another reimbursement pathway. Then diagnose coverage policy, prior authorization, step therapy, site of care, provider economics, patient affordability, and evidence gaps instead of assuming every product is a PBM tier-negotiation case.

Relevant published work: ZS, Huron, and IQVIA publish on market access, evidence, analytics, or commercialization.

4. Pharma/Biotech M&A and Due Diligence

A large pharma company is evaluating acquiring a mid-size biotech with a Phase III asset. Is it worth the purchase price? This requires rNPV modeling, competitive landscape analysis, commercial potential sizing, and integration risk assessment.

Relevant published work: L.E.K., BCG, and McKinsey publish on biopharma strategy, transactions, or portfolio choices.

5. Medical Device Market Sizing

How large is the addressable market for a new surgical robot? A continuous glucose monitor? This is a medical device version of the standard market sizing framework but requires knowledge of procedure volumes, hospital purchasing dynamics, and reimbursement codes (CPT codes, DRG groupings).

Relevant published work: MedTech, healthcare, and strategy practices across several firms publish on sizing, adoption, and reimbursement.

Firms That Specialize in Life Sciences Consulting

Candidate reports for L.E.K. mention market sizing and strategic assessment, while third-party ZS guides describe commercial, market-access, pricing, and salesforce prompts. Treat both as directional reports rather than firm-wide rules. Huron's published work supports healthcare-operations and commercialization practice themes, but not a guaranteed interview inventory.

Essential Life Sciences Terminology

Before your interview, you must know these terms well enough to use them naturally, not just define them when asked.

Understanding PBM mechanics and formulary dynamics matters when the prompt names a pharmacy-benefit product. PBMs negotiate coverage and rebate arrangements for many retail and specialty drugs. Physician-administered products may instead require medical-benefit coverage, prior authorization, site-of-care analysis, provider reimbursement, and buy-and-bill economics. Identify the channel before applying the framework.

Patent cliffs are equally critical: branded drugs can lose revenue quickly after generic or biosimilar entry, especially when multiple competitors enter and substitution is easy. This makes life-cycle management (reformulations, new indications, combination products) a recurring case topic.

Fictional Worked Example: Oncology Drug Launch Strategy

Every product, competitor, access condition, and figure below is a supplied assumption for this fictional exercise.

Prompt: "Your client, a mid-size biotech, received FDA approval 6 months ago for a new PD-L1 inhibitor in second-line non-small cell lung cancer (NSCLC). Sales are tracking 40% below forecast. What's going wrong, and what should they do?"

Step 1: Clarify the situation

• What is the target patient population size, and how many patients have been identified and treated?
• How is the infused product covered across commercial and Medicare medical benefits, and where are denials or delays occurring?
• How does the drug compare with the established standard of care and other prompt-supplied competitors on efficacy, safety, access, and price?
• Is there a companion diagnostic required (i.e., PD-L1 expression test before prescribing)?

Step 2: Market assessment

Step 3: Pricing and market access diagnosis

If sales are 40% below forecast, useful hypotheses to test in a biotech launch include:

1. Restrictive medical policy or site-of-care rules: coverage criteria, coding, provider reimbursement, or infusion-site requirements make the product harder to start
2. Prior-authorization burden: documentation and appeal requirements slow time to treatment and create abandonment
3. Evidence gap: payers or providers do not see enough comparative clinical, economic, or real-world evidence to change established treatment behavior

Step 4: Commercial model gaps

• Is the salesforce appropriately sized for oncology (smaller, specialist-focused)?
• Are medical science liaisons (MSLs) engaging with the right academic medical centers?
• Is there a robust patient services program helping patients navigate prior authorization?

Step 5: Recommendations

Immediate (0 to 3 months): Analyze approval, denial, appeal, time-to-treatment, site-of-care, and provider-reimbursement data by payer. Fix the operational access failures first, then address the specific coverage-policy or evidence objection each payer raises. Expand patient services where affordability or navigation is causing abandonment.

Medium-term (3 to 12 months): Build comparative real-world and economic evidence against the relevant standard of care, then use it in medical-policy reviews, health-technology discussions, and provider education. The exact evidence plan depends on the label, endpoint, available data, and objections found in the case.

Long-term: Evaluate a biomarker-defined first-line label expansion. It may expand the eligible population, but it also enters a highly competitive treatment setting and requires a credible clinical-development and differentiation plan.

Illustrative case assumptions: Suppose the prompt gives 10,000 eligible patients, a 15% incremental treated share after access improvements, and $150,000 in annual net revenue per treated patient. That is 1,500 incremental patients and $225 million in annual net revenue before persistence, ramp, gross-to-net, and capacity adjustments. These are case inputs, not market facts.

Probability-weighted math for pharma cases

Probability-weighted math adjusts each future cash flow by the chance the drug actually reaches that point. It is the core of rNPV, and interviewers use it in pipeline and M&A cases. Here is an original example with case inputs only.

Prompt: A Phase II asset would earn $500M in peak annual sales at a 30% operating margin if approved. The case gives these chances of success: Phase II 40%, Phase III 60%, approval 90%. Phase III costs $200M and only happens if Phase II succeeds.

1. Chance of reaching market: 40% x 60% x 90% = 21.6%.
2. Peak annual profit if approved: $500M x 30% = $150M.
3. Probability-weighted peak profit: 21.6% x $150M = about $32M a year.
4. Probability-weighted Phase III cost: 40% x $200M = $80M, because the money is only spent if Phase II works.

The insight: the unadjusted view says "$150M a year of profit", while the weighted view says about $32M a year against an expected $80M Phase III bill, before discounting for time. Say this out loud in a case, then ask the interviewer for the discount rate and launch year if they want a full rNPV.

Common Mistakes in Life Sciences Cases

1. Treating the FDA process as a black box. Saying "the drug gets approved and then you launch" misses the commercial preparation that may begin during clinical development. The sequence and timing depend on the asset, indication, evidence plan, regulatory path, and company.

2. Ignoring access dynamics. Assuming that physician recommendation alone drives use misses coverage policy, prior authorization, benefit design, site of care, provider economics, and patient affordability. Apply only the mechanisms relevant to the product in the prompt.

3. Using generic market sizing without understanding patient identification. A pharma market sizing must account for diagnosed vs. undiagnosed patients, treatment-eligible vs. non-eligible subsets, and patient identification rates. Not all patients in the "addressable" population are actually treated.

4. Conflating WAC and net price. WAC is the list price, while realized net price can differ after rebates, discounts, and other concessions. Do not assume one rebate percentage across therapeutic areas or contracts; ask for the case data.

5. Missing the biosimilar/generic timeline. If the drug being launched is a biologic with LOE in 5 years, that changes the commercial forecast horizon and NPV calculation fundamentally.

Readiness-Based Prep Plan for Life Sciences Candidates

Stage 1: Industry foundation

• Read Hacking the Case Interview's life sciences guide end-to-end
• Study FDA regulatory pathways: IND → Phase I → Phase II → Phase III → NDA/BLA → approval
• Learn the difference between pharmacy-benefit and medical-benefit access, including PBMs, formularies, prior authorization, site of care, and provider reimbursement
• Review pharma case interview examples and healthcare case interview prep

Stage 2: Core frameworks

• Practice the 4-part drug launch structure (market, pricing, access, commercial)
• Learn rNPV mechanics for pipeline/M&A cases
• Practice medical device market sizing with procedure volume data
• Review the market sizing framework and profitability framework for adaptation to life sciences

Stage 3: Case practice with terminology

• Solve fresh drug-launch cases until you can tailor the market, pricing, access, and commercial-model structure to the evidence
• Practice market-access cases across different channels, such as a retail pharmacy product and a physician-administered therapy, until you can explain why the channel changes the analysis
• Complete M&A or due-diligence practice with rNPV framing when the prompt includes clinical-development risk
• Run one Road to Offer case rep and debrief whether your recommendation connected clinical evidence, payer access, and commercial execution
• Review the ZS Associates case interview guide and L.E.K.-specific case format notes

Stage 4: Integrated rehearsal and firm-specific prep

• Run full mock interviews with a partner using the case interview practice partner guide until your recurring structure, quantitative, and synthesis errors stabilize
• Review McKinsey's public GlobaPharm case (available on McKinsey's careers page), an excellent life sciences case with HEOR and market access elements
• Prepare evidence-rich behavioral stories relevant to the role, such as managing complexity, working across payer/provider/patient stakeholders, and making data-driven decisions
• Study Huron consulting case interview guide for healthcare operations case types

Related Guides

• Pharma Case Interview Guide
• Healthcare Case Interview Guide
• Pricing Strategy Cases: drug pricing, payer negotiations, and value-based contracts are core to life sciences commercial strategy
• PE Due Diligence Framework: the diligence layer for pipeline and asset M&A
• Market Sizing Framework
• Unit Economics Framework

Sources (reviewed July 20, 2026)

1. Life Sciences Consulting Case Interview: Complete Guide (Hacking the Case Interview)
2. ZS Case Interview: The Complete Prep Guide 2026 (Hacking the Case Interview)
3. L.E.K. Consulting Life Science Associate Interview Questions (Glassdoor)
4. Pharma Case Interview Practice (ZS Associates)
5. PBMs, Formularies, and Rebates: What Investors Should Know (DrugPatentWatch)
6. Patent Cliff Playbook: Formulary Management in the Age of Generic Entry (DrugPatentWatch)
7. Valuing Pharmaceutical Assets: When to Use NPV vs rNPV (Alacrita)
8. Pharma Case Interview Example (Management Consulted)
9. Managing the Pharmacy Benefit: The Formulary System (PMC)