Ethan Heffernan

Pharmaceutical Product Concentration: Measuring Revenue Dependence in Major U.S. Drugmakers

Working paper
Keywords: concentration risk, CR3, CR5, HHI, pharma
Methods: CR3, CR5, HHI, synthetic HHI
Software: Excel, Python, Astro

This working paper quantifies how concentrated pharmaceutical revenues have become among the five largest U.S.-listed drug manufacturers—AbbVie, Bristol Myers Squibb, Johnson & Johnson, Merck, and Pfizer. Using public segment disclosures from 2022–2024, the study applies conventional concentration metrics (CR3, CR5, HHI) and introduces interval-bounded estimates to account for the opacity of aggregated "Other" revenue categories.

By treating undisclosed revenue segments as synthetic products, the approach yields upper and lower bounds for concentration that reflect both reporting heterogeneity and genuine economic exposure. Differences in disclosure practice alone can change perceived concentration risk by double-digit percentages — an important consideration for valuation, antitrust analysis, and portfolio risk assessment.

1. Introduction

Product concentration risk is the degree to which a firm’s revenue relies on a small fraction of their products portfolio. This reliance creates a risk for firms as a relatively small change in the cash flows from a product they are concentrated in has an outsized effect on the firm as a whole. The greater the proportion of revenues attributable to top-selling products, the greater the product concentration risk. In the pharmaceutical industry, shocks to these product revenues typically involve patent cliffs, safety concerns, and competitive entries.

This report describes the product concentration in the pharmaceutical divisions of the five largest U.S.-listed pharmaceutical companies by annual revenue as of 2024 using segmented revenues from their annual reports. Product concentrations are measured using three standard measures: CR3, CR5, and an extension of the Herfindahl–Hirschman Index (HHI). Due to variations in revenue disclosure transparency, interval estimates are provided for each.

2. Methods

2.1 Data

Itemized product revenues were sourced from annual reports published on the company websites of the firms we chose to study. Each company under study published segmented revenue sources in the notes to the financial statements for 2024 and the two years prior. The granularity of revenue segmentation varied between companies.

A portion of revenues were attributed to aggregated items for every company in our study. The components of these aggregated items were generally not listed in the footnotes; instead, a generic description was provided. The proportion of revenues from named products and product families as compared to those in aggregated items showed significant variation between firms.

Among these aggregated items:

  • Some companies’ reporting decomposed aggregated revenues into subcategories of pharmaceutical revenue to which they were attributable (e.g., “All other Oncology”).
  • Others did not (e.g., “Other Pharmaceutical”).

In accordance with accounting norms, annual reports for FY 2024 included retrospective application of that year’s segmentation for the two previous years’ data.

2.2 Definitions

We define product shares using reported product-level revenues within each firm’s pharmaceutical division with total division revenue. Concentrations are defined, by convention, as:

[ \text{Concentration Ratio} = \frac{\text{Revenue of Top k Products}}{\text{Total Division Revenue}} ]

We report interval estimates for all product concentration measures. The distribution of product shares within aggregated categories was not disclosed by any company and is impossible to backform in the absence of other information.

  • CR3 and CR5 are left-tail truncation-insensitive top-k measures. Their values are only affected by the items selected and the size of the population they’re drawn from. Selecting aggregated items as part of these ratios is not prudent as their contents are opaque.

    • Upper bound estimate → treats aggregated items as a single synthetic product
    • Lower bound estimate → removes them from consideration entirely

Unlike CR3 and CR5, HHI is distribution-sensitive with a change in any component affecting the index. Resultantly, we cannot drop aggregated categories entirely without distorting the measure.

  • HHI Upper Bound: includes each aggregated item as a single synthetic product
  • HHI Lower Bound: partitions aggregated items into synthetic products, each smaller than the smallest reported product share in that category (if applicable)

2.3 Rationale

We intentionally avoid reporting a normalized HHI, which would entail rescaling the index to reduce the effect of the total number of items in favor of quantifying relative scale.

In pharmaceutical product concentration:

  • The number of unique products
  • The opacity of aggregated items

…illuminate the concentration risks the company faces.

Calculating upper and lower bounds for HHI via disaggregation of roll-up items is more informative to the theoretical best- and worst-case scenarios underlying the reported data. This approach preserves information about product count and concentration for reported line items.

3. Results

Table 1. Product Concentration Ratios (High vs Low Estimates)

YearFirmCR3 (High)CR5 (High)HHI (High)CR3 (Low)CR5 (Low)HHI* (Low)
2024JNJ0.46090.578610040.46090.5786994
2024MRK0.70690.780929390.70640.76042920
2024BMY0.58820.737814640.58820.73781449
2024PFE0.31240.48556470.31240.4855576
2024ABBV0.47360.591310100.47360.5913976
2023JNJ0.45140.56859640.45140.5685953
2023MRK0.67840.763025630.67840.75382545
2023BMY0.60690.763315120.60690.76331500
2023PFE0.42010.57938610.42010.5588776
2023ABBV0.48120.603211710.48120.60241132
2022JNJ0.41550.53828690.41550.5382850
2022MRK0.64450.745920250.64450.74172003
2022BMY0.65030.801116150.65030.80111603
2022PFE0.63330.748119550.63330.74811923
2022ABBV0.53350.651616490.53350.62531594

HHI denotes the lower-bound estimate.

4. Figures

  • Figure 1. CR3 and CR5 for Segmented Pharmaceutical Product Concentrations
  • Figure 2. Herfindahl–Hirschman Index for Segmented Pharmaceutical Product Concentrations

Highlighted are the uninformative items from the segmented revenues included in the notes to the financial statements. Three of the five largest pharmaceutical firms have aggregated product categories listed in the top five of their pharmaceutical revenues when sorted by annual revenue. Financial reporting regulations dictate minimum disclosure standards.

5. Discussion

(Draft section — not yet filled in)

Appendix

Table 2. Leading Reported Product Categories

Johnson & Johnson

Rank202220232024
1StelaraStelaraDarzalex
2DarzalexDarzalexStelara
3Invega Sustenna…Invega Sustenna…Invega Sustenna…
4ImbruvicaImbruvicaTremfya
5TremfyaTremfyaImbruvica

Merck & Co.

Rank202220232024
1KeytrudaKeytrudaKeytruda
2Gardasil/Gardasil 9Gardasil/Gardasil 9Gardasil/Gardasil 9
3LagevrioProQuad/M-M-R II…Other pharmaceutical
4JanuviaOther pharmaceuticalProQuad/M-M-R II…
5Other pharmaceuticalJanuviaBridion

Bristol Myers Squibb

Rank202220232024
1EliquisEliquisEliquis
2RevlimidOpdivoOpdivo
3OpdivoRevlimidRevlimid
4Pomalyst/ImnovidOrenciaOrencia
5OrenciaPomalyst/ImnovidPomalyst/Imnovid

Pfizer

Rank202220232024
1ComirnatyComirnatyEliquis
2PaxlovidEliquisPrevnar family
3EliquisPrevnar familyPaxlovid
4Prevnar familyIbranceVyndaqel family
5IbranceAll other HospitalComirnaty

AbbVie

Rank202220232024
1HumiraHumiraSkyrizi
2SkyriziSkyriziHumira
3ImbruvicaRinvoqRinvoq
4All otherImbruvicaImbruvica
5Botox TherapeuticAll otherBotox Therapeutic

Citations

  • 17 CFR § 210.5-03
  • Interval Estimation of the Herfindahl–Hirschman Index under Incomplete Market Information (ResearchGate)

Draft: October 2025