# Certara, Inc. (CERT)

Informational only - not investment advice.

CIK: 0001827090
SIC: 7372 Services-Prepackaged Software
SIC breadcrumb: [Services](/division/I/) > [Business Services](/major-group/73/) > [SIC 7372 Services-Prepackaged Software](/industry/7372/)
Latest 10-K filed: 2026-02-26
SEC page: https://www.sec.gov/edgar/browse/?CIK=1827090
Filing source: https://www.sec.gov/Archives/edgar/data/1827090/000182709026000011/cert-20251231.htm

## At a glance

FY2025 · period end 2025-12-31 · filed 2026-02-26 · accession 0001827090-26-000011 · source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001827090.json

| Metric | Value | FY | Provenance |
| --- | ---: | ---: | --- |
| Revenue | 418,838,000 USD | 2025 | verified |
| Net income | -1,595,000 USD | 2025 | verified |
| Assets | 1,556,582,000 USD | 2025 | verified |
| Free cash flow | 94,565,000 USD | 2025 | computed |
| Net margin | -0.38% | 2025 | computed |
| Operating margin | 5.02% | 2025 | computed |
| Revenue YoY | +8.75% | 2025 | computed |
| ROE | -0.15% | 2025 | computed |

Computed values are grepcent-computed from the verified facts above and may differ from ratios the company itself reports. Free cash flow = operating cash flow − capital expenditures. Net margin = net income ÷ revenue. Operating margin = operating income ÷ revenue. Revenue YoY = FY2025 revenue ÷ FY2024 revenue − 1 (consecutive fiscal years only). ROE = net income ÷ period-end stockholders' equity.

No market price, no rating, no forecast on this site. Not investment advice.

### Peer percentile fingerprint

| Ratio | CERT | Peer median | Percentile | N |
| --- | ---: | ---: | ---: | ---: |
| Net margin | -0.4% | 1.5% | 44 | 122 |
| Operating margin | 5.0% | 1.3% | 58 | 121 |
| Revenue growth | 8.7% | 13.5% | 32 | 124 |
| FCF margin | 22.6% | 19.3% | 61 | 120 |
| ROE | -0.2% | 2.0% | 45 | 112 |
| ROA | -0.1% | 0.9% | 45 | 124 |
| Liabilities / equity | 0.46 | 0.91 | 20 | 113 |
| Current ratio | 2.05 | 1.57 | 70 | 124 |

Percentile = share of the N covered peers reporting that ratio whose value is lower (ties counted half); computed among grepcent-covered companies in SIC industry 7372 Services-Prepackaged Software, not the whole market. A higher percentile means a higher value of the ratio, not a better company. Ratios with fewer than 8 reporting peers are omitted. Latest reported values per company; fiscal periods may differ. Descriptive arithmetic - not a score, rating, or ranking.

## Selected Fundamentals
| Metric | Value | Unit | FY | Filed |
| --- | ---: | --- | ---: | --- |
| Revenue | 418838000 | USD | 2025 | 2026-02-26 |
| Net income | -1595000 | USD | 2025 | 2026-02-26 |
| Assets | 1556582000 | USD | 2025 | 2026-02-26 |

## Financials

Annual standardized facts from SEC companyfacts as of latest extracted filing date 2026-02-26. Source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001827090.json. Derived margins, ratios, and free cash flow are computed from the extracted annual SEC facts.

| Metric | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 |
| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| Revenue |  | 208,511,000 | 243,530,000 | 286,104,000 | 335,644,000 | 354,337,000 | 385,148,000 | 418,838,000 |
| Net income |  | -8,926,000 | -49,397,000 | -13,266,000 | 14,731,000 | -55,357,000 | -12,051,000 | -1,595,000 |
| Operating income |  | 19,613,000 | -24,420,000 | 13,579,000 | 32,521,000 | -40,774,000 | -1,731,000 | 21,016,000 |
| Diluted EPS |  | -0.07 | -0.37 | -0.09 | 0.09 | -0.35 | -0.08 | -0.01 |
| Operating cash flow |  | 38,025,000 | 44,810,000 | 60,388,000 | 92,543,000 | 82,755,000 | 80,466,000 | 96,325,000 |
| Capital expenditures |  | 2,107,000 | 863,000 | 1,143,000 | 1,430,000 | 1,777,000 | 1,625,000 | 1,760,000 |
| Share buybacks |  | 703,000 | 1,079,000 |  |  | 0.00 | 0.00 | 42,610,000 |
| Assets |  |  | 1,269,400,000 | 1,511,730,000 | 1,572,922,000 | 1,563,140,000 | 1,575,104,000 | 1,556,582,000 |
| Liabilities |  |  | 447,268,000 | 469,881,000 | 493,261,000 | 516,300,000 | 516,448,000 | 493,787,000 |
| Stockholders' equity | 492,769,000 | 492,048,000 | 822,132,000 | 1,041,849,000 | 1,079,661,000 | 1,046,840,000 | 1,058,656,000 | 1,062,795,000 |
| Cash and cash equivalents |  | 29,256,000 | 271,382,000 | 185,797,000 | 236,586,000 | 234,951,000 | 179,183,000 | 189,392,000 |
| Free cash flow |  | 35,918,000 | 43,947,000 | 59,245,000 | 91,113,000 | 80,978,000 | 78,841,000 | 94,565,000 |

### Ratios

ROE and ROA use period-end equity/assets. Liabilities / equity uses total liabilities divided by stockholders' equity. Current ratio uses current assets divided by current liabilities when both are reported.

| Metric | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 |
| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| Net margin |  | -4.28% | -20.28% | -4.64% | 4.39% | -15.62% | -3.13% | -0.38% |
| Operating margin |  | 9.41% | -10.03% | 4.75% | 9.69% | -11.51% | -0.45% | 5.02% |
| Return on equity |  | -1.81% | -6.01% | -1.27% | 1.36% | -5.29% | -1.14% | -0.15% |
| Return on assets |  |  | -3.89% | -0.88% | 0.94% | -3.54% | -0.77% | -0.10% |
| Liabilities / equity |  |  | 0.54 | 0.45 | 0.46 | 0.49 | 0.49 | 0.46 |
| Current ratio |  |  | 4.60 | 2.98 | 3.32 | 2.62 | 2.13 | 2.05 |

## As-reported value updates

No tracked differences above grepcent's stated thresholds and capped precision rule were found between the earliest XBRL-filed value and the value currently on file for the standardized annual metrics grepcent tracks.


## Quarterly

Quarterly standardized facts from SEC companyfacts as of latest extracted filing date 2026-08-04. Source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001827090.json.

Flow metrics use discrete quarter-length periods from 10-Q/10-Q/A filings. Q4 revenue and net income are derived only when annual FY and nine-month YTD facts exist for the same fiscal year; derived Q4 values are labeled. EPS Q4 is not derived.

| Quarter | End date | Revenue | Net income | Diluted EPS | Method |
| --- | --- | ---: | ---: | ---: | --- |
| 2022-Q3 | 2022-09-30 |  |  | 0.02 | reported discrete quarter |
| 2023-Q1 | 2023-03-31 |  |  | 0.01 | reported discrete quarter |
| 2023-Q2 | 2023-06-30 |  |  | 0.03 | reported discrete quarter |
| 2023-Q3 | 2023-09-30 | 85,576,000 | -48,965,000 | -0.31 | reported discrete quarter |
| 2023-Q4 | 2023-12-31 | 88,010,000 | -12,456,000 |  | derived Q4 = FY annual - nine-month YTD |
| 2024-Q1 | 2024-03-31 | 96,654,000 | -4,683,000 | -0.03 | reported discrete quarter |
| 2024-Q2 | 2024-06-30 | 93,313,000 | -12,574,000 | -0.08 | reported discrete quarter |
| 2024-Q3 | 2024-09-30 | 94,820,000 | -1,371,000 | -0.01 | reported discrete quarter |
| 2024-Q4 | 2024-12-31 | 100,361,000 | 6,577,000 |  | derived Q4 = FY annual - nine-month YTD |
| 2025-Q1 | 2025-03-31 | 106,004,000 | 4,743,000 | 0.03 | reported discrete quarter |
| 2025-Q2 | 2025-06-30 | 104,570,000 | -1,968,000 | -0.01 | reported discrete quarter |
| 2025-Q3 | 2025-09-30 | 104,616,000 | 1,525,000 | 0.01 | reported discrete quarter |
| 2025-Q4 | 2025-12-31 | 103,648,000 | -5,895,000 |  | derived Q4 = FY annual - nine-month YTD |
| 2026-Q1 | 2026-03-31 | 106,915,000 | -8,763,000 | -0.06 | reported discrete quarter |
| 2026-Q2 | 2026-06-30 | 93,271,000 | -55,270,000 | -0.36 | reported discrete quarter |

## Filed narrative (10-K & 10-Q)

## Business

Verbatim Item 1 Business section from CERT's latest 10-K: [/company/CERT/business/](/company/CERT/business/).

## Risk Factors

Verbatim Item 1A Risk Factors from CERT's latest 10-K: [/company/CERT/risk-factors/](/company/CERT/risk-factors/).

## Latest quarter (10-Q)

Latest 10-Q source: https://www.sec.gov/Archives/edgar/data/1827090/000182709026000028/cert-20260630.htm

Extracted structurally from real Item 2 body heading to real Item 3/4 boundary.
Confidence: high
Filing date: 2026-08-04
Report date: 2026-06-30

Item 2. Management’s Discussion and Analysis of Financial Condition and Results of Operations

The following discussion summarizes the significant factors affecting the operating results, financial condition, liquidity, and cash flows of our Company as of and for the periods presented below. The following discussion and analysis should be read in conjunction with the unaudited condensed consolidated financial statements and the related notes thereto included elsewhere in this Quarterly Report and our 2025 Annual Report. The statements in this discussion regarding industry outlook, our expectations regarding our future performance, liquidity, and capital resources, and all other non-historical statements in this discussion are forward-looking statements and are based on the beliefs of our management, as well as assumptions made by, and information currently available to, our management. Actual results could differ materially from those discussed in or implied by forward-looking statements as a result of various factors, including those discussed below and elsewhere in this Quarterly Report, particularly in the section “Special Note Regarding Forward-Looking Statements” of this Quarterly Report.

We intend the discussion of our financial condition and results of operations that follows to provide information that will assist the reader in understanding our condensed consolidated financial statements, the changes in certain key items in those financial statements from period to period, and the primary factors that accounted for those changes, as well as how certain accounting principles, policies, and estimates affect our condensed consolidated financial statements.

Executive Overview

We are a global leader in biosimulation science, technology and consulting services for using Model-Informed Drug Development (“MIDD”) in the global biopharmaceutical and biotech industry. MIDD is an approach that utilizes biological and statistical models derived from preclinical, clinical, and evidence data to inform decision-making in drug research and development, and commercialization. Biosimulation is a critical component of MIDD that uses computer-aided mathematical simulation of biological processes and systems to understand the action of a drug in a human body or a population of humans. Our goal is to enable the life science industry to use data, modeling, and analytics to make better decisions during drug research, development and commercialization to increase productivity rates and vastly reduce development costs.

Drug development is necessarily a highly regulated process involving the collection of vast amounts of laboratory, clinical and evidence data, and there are many failures at every step along the way that add to total cost. On average, the pharmaceutical industry spends more than $290 billion annually on research and development (“R&D”). Generally, companies spend an average of $6.2 billion per FDA-approved drug to develop one new medicine, including the cost of failures, according to “Analysis of pharma R&D productivity -

37

a new perspective needed” on Drug Discovery Today. Our technology and scientists incorporate modern advances in scientific understanding, drug research and development experience, data analysis, and AI, resulting in significant opportunities to decrease the cost and increase the odds of new drug approval and commercial success.

Our approach to AI is grounded in our long-standing expertise in mechanistic and empirical modeling. We deploy AI capabilities within validated scientific frameworks and expert-led workflows, rather than as standalone automated systems. This expert-in-the-loop model allows us to leverage native AI capabilities in a manner that is consistent with regulatory expectations for transparency, reproducibility, and explainability.

Our proprietary biosimulation platforms are built on biology, chemistry, and pharmacology principles with proprietary mathematical algorithms that model how medicines and diseases behave in the body. For over two decades, our scientists have developed and validated our biosimulation technology using data from scientific literature, laboratory research, preclinical and clinical studies. To do this, we have developed scientifically based solutions for the collection, standardization, validation, storage, and analysis of the preclinical, clinical and evidence data needed for MIDD. These data solutions are used internally and industry wide by life sciences companies.

Native AI and machine learning technologies are being incorporated across our technology and consulting services portfolios, providing opportunities to expand the number of data sources utilized, better predict outcomes, and streamline reporting. For example, we are using machine learning to automate and speed the process of biosimulation.

We apply AI capabilities within established modeling environments and under the supervision of experienced scientists and regulatory experts. Our modeling platforms, curated datasets, and regulatory experience position us to incorporate emerging AI techniques in a controlled and scientifically rigorous manner. While AI can enhance productivity and insight generation, our solutions continue to rely on validated models and expert interpretation to support decision-making in regulated environments.

We leverage our validated software applications to deliver technology-enabled services. Our services are delivered by scientists with extensive drug development experience who aid our customers in applying biosimulation and MIDD to their specific projects.

Since 2014, customers who leverage our solutions have received 90% or more of all new drug approvals by FDA. We have worked with more than 2,600 life sciences companies and academic institutions and have collaborated on more than 10,000 customer projects in the last decade across a wide variety of therapeutic areas ranging from cancer and hematology to diabetes and hundreds of rare diseases. Our software products are licensed by more than 160,000 users and are also used by 20 global drug regulatory agencies, including the FDA, the UK’s MHRA, Japan's PMDA, and China’s NMPA.

With continued innovation in and adoption of our biosimulation software, technology, and services, we believe more life science companies worldwide will leverage more of our end-to-end platform to reduce cost, accelerate speed to market, and ensure safety and efficacy of medicines for all patients.

Key Factors Affecting Our Performance

We believe that the growth and future success of our business depend on many factors. While each of these factors presents significant opportunities for our business, they also pose important challenges that we must successfully address to sustain our growth and improve the results of our operations.

38

Customer Retention and Expansion

Our future operating results depend, in part, on our ability to successfully enter new markets, increase our customer base, and retain and expand our relationships with existing customers. We monitor two key performance indicators to evaluate retention and expansion: new bookings and net retention rates.

•Bookings: Our new bookings represent the estimated contract value of a signed contract or purchase order where there is sufficient or reasonable certainty about the customer’s ability and intent to fund and commence the software and/or services. Bookings vary from period to period depending on numerous factors, including the overall health of the biopharmaceutical industry, regulatory developments, industry consolidation, and sales performance. Bookings have varied and will continue to vary significantly from quarter to quarter and from year to year.

•Net Retention Rates: Our net retention rates measure the percentage of recurring revenue that is retained from existing software customers over a specific period of time, inclusive of price increases and expansion, excluding revenue from acquisitions occurred within the past 12 months.

The table below summarizes our quarterly bookings and net software retention rate trends from continuing operations:

[[GREPCENT_TABLE]]
[["","","2026","","2025"],["","","Q1","","Q2","","Q1","","Q2"],["","","(in millions except percentage)"],["Bookings","","$","97.2","","","$","98.3","","","$","98.4","","","$","97.4"],["Net Retention Rates","","106.1","%","","101.5","%","","102.4","%","","107.6","%"]]
[[/GREPCENT_TABLE]]

Investments in Growth

We have invested and intend to continue to invest in expanding the breadth and depth of our solutions, including through acquisitions and international expansion. We expect to continue to invest in (i) scientific talent to expand our ability to deliver solutions across the drug development spectrum; (ii) sales and marketing to promote our solutions to new and existing customers and in existing and expanded geographies; (iii) research and development to support existing solutions and innovate new technology; (iv) other operational and administrative functions to support our expected growth; and (v) complementary business.

Our Operating Environment

The acceptance of model-informed biopharmaceutical discovery and development by regulatory authorities affects the demand for our products and services. Support for the use of biosimulation in discovery and development from regulatory bodies, such as the FDA and EMA, has been critical to its rapid adoption by the biopharmaceutical industry. There has been a steady increase in the recognition by regulatory and academic institutions of the role that modeling and simulation can play in the biopharmaceutical development and approval process, as demonstrated by new regulations and guidance documents describing and encouraging the use of modeling and simulation in the biopharmaceutical discovery, development, testing, and approval process, which has directly led to an increase in the demand for our services. Changes in government or regulatory policy, or a reversal in the trend toward increasing the acceptance of and reliance upon in silico data in the drug approval process, could decrease the demand for our products and services or lead regulatory authorities to cease use of, or recommend against the use of, our products and services.

39

Governmental agencies throughout the world, but particularly in the United States where the majority of our customers are based, strictly regulate the biopharmaceutical development process. Our business involves helping biopharmaceutical companies strategically and tactically navigate the regulatory approval process. New or amended regulations are expected to result in higher regulatory standards and often additional revenues for companies that service these industries. However, some changes in regulations, such as a relaxation in regulatory requirements or the introduction of streamlined or expedited approval procedures, or an increase in regulatory requirements that we have difficulty satisfying or that make our regulatory strategy services less competitive, could eliminate or substantially reduce the demand for our regulatory services.

Additionally, changes in government leadership may also result in either stricter or more relaxed regulatory environments. In the United States, recent executive actions and related government initiatives concerning prescription drug pricing, together with existing statutes and implementing guidance, may create additional uncertainty in pricing frameworks. For example, government-led initiatives to expand direct-to-consumer discount mechanisms and other pricing programs could alter market dynamics and may indirectly affect customer research and development investment levels and priorities. Furthermore, in the past year, there has been a general pullback of government support and funding for drug development, particularly for public sector and academic organizations, dependent on outside funding to develop early-stage research. Any material d

[Excerpt truncated for page length; source filing is linked above.]

## Latest 10-K MD&A (excerpt)

Latest 10-K Item 7 source: https://www.sec.gov/Archives/edgar/data/1827090/000182709026000011/cert-20251231.htm
Complete FY 2025 MD&A: /company/CERT/mda/fy2025/

Extracted structurally from real Item 7 body heading to real Item 7A/8 boundary.
Confidence: high
Filing date: 2026-02-26
Report date: 2025-12-31

Item 7. Management’s Discussion and Analysis of Financial Condition and Results of Operations.

For purposes of this Management's Discussion and Analysis of Financial Condition and Results of Operations section, we use the terms "Certara Inc.", "Company", “we”, “us”, and “our” to refer to Certara, Inc.

You should read the following discussion of our financial condition and results of operations in conjunction with our audited consolidated financial statements and the related notes and other financial information included elsewhere in this Annual Report and our audited consolidated financial statements and notes thereto.

As discussed in the section titled “Special Note Regarding Forward Looking Statements,” the following discussion and analysis, in addition to historical financial information, contains forward-looking statements that involve risks and uncertainties. Our actual results could differ materially from those anticipated in these forward-looking statements as a result of various factors, including those set forth in the section titled “Risk Factors” under Part I, Item 1A above. For a discussion of our financial condition and results of operations for the year ended December 31, 2024 compared to the year ended December 31, 2023, see “Results of Operations” and “Liquidity and Capital Resources” under Part II, Item 7. Management’s Discussion and Analysis of Financial Condition and Results of Operations in our 2024 Annual Report on Form 10-K.

We intend the discussion of our financial condition and results of operations that follows to provide information that will assist the reader in understanding our consolidated financial statements, the changes in certain key items in those financial statements from year to year, and the primary factors that accounted for those changes, as well as how certain accounting principles, policies and estimates affect our Consolidated Financial Statements.

Executive Overview

We are a global leader in biosimulation science, technology and consulting services for using Model-Informed Drug Development (“MIDD”) in the global biopharmaceutical and biotech industry. MIDD is an approach that utilizes biological and statistical models derived from preclinical, clinical, and evidence data to inform decision-making in drug research and development, and commercialization. Biosimulation is a critical component of MIDD that uses computer-aided mathematical simulation of biological processes and systems to understand the action of a drug in a human body or a population of humans. Our goal is to enable the life science industry to use data, modeling, and analytics to make better decisions during drug research, development and commercialization to increase productivity rates and vastly reduce development costs.

Drug development is necessarily a highly regulated process involving the collection of vast amounts of laboratory, clinical and evidence data, and there are many failures at every step along the way that add to total cost. On average, the pharmaceutical industry spends more than $290 billion annually on research and development(“R&D”). Generally, companies spend an average of $6.2 billion per FDA-approved drug to develop one new medicine, including the cost of failures, according to “Analysis of pharma R&D productivity - a new perspective needed” on Drug Discovery Today. Our technology and scientists incorporate modern advances in scientific understanding, drug research and development experience, data analysis, and AI, resulting in significant opportunities to decrease the cost and increase the odds of new drug approval and commercial success.

Our approach to AI is grounded in our long-standing expertise in mechanistic and empirical modeling. We deploy AI capabilities within validated scientific frameworks and expert-led workflows, rather than as standalone automated systems. This expert-in-the-loop model allows us to leverage native AI capabilities in a manner that is consistent with regulatory expectations for transparency, reproducibility, and explainability.

56

Table of Contents

Our proprietary biosimulation platforms are built on biology, chemistry, and pharmacology principles with proprietary mathematical algorithms that model how medicines and diseases behave in the body. For over two decades, our scientists have developed and validated our biosimulation technology using data from scientific literature, laboratory research, preclinical and clinical studies. To do this, we have developed scientifically based solutions for the collection, standardization, validation, storage, and analysis of the preclinical, clinical and evidence data needed for MIDD. These data solutions are used internally and industry wide by life sciences companies.

The scientific principles underlying our work must be transparent and fully explainable during the regulatory process, so we have developed expertise in incorporating data, references and results into regulatory documents. Our software and regulatory scientific services streamline the creation of regulatory filings and speed regulatory data flow to maximize the chances of successful commercialization.

Native AI and machine learning technologies are being incorporated across our technology and consulting services portfolios, providing opportunities to expand the number of data sources utilized, better predict outcomes, and streamline reporting. For example, we are using machine learning to automate and speed the process of biosimulation, and we have created generative AI applications to aid in drafting regulatory documents from scientific analyses and clinical data.

We apply AI capabilities within established modeling environments and under the supervision of experienced scientists and regulatory experts. Our modeling platforms, curated datasets, and regulatory experience position us to incorporate emerging AI techniques in a controlled and scientifically rigorous manner. While AI can enhance productivity and insight generation, our solutions continue to rely on validated models and expert interpretation to support decision-making in regulated environments.

We leverage our validated software applications to deliver technology-enabled services. Our services are delivered by scientists with extensive drug development experience who aid our customers in applying biosimulation and MIDD to their specific projects.

Since 2014, customers who leverage our solutions have received 90% or more of all new drug approvals by FDA. We have worked with more than 2,600 life sciences companies and academic institutions and have collaborated on more than 10,000 customer projects in the last decade across a wide variety of therapeutic areas ranging from cancer and hematology to diabetes and hundreds of rare diseases. Our software products are licensed by more than 160,000 users and are also used by 20 global drug regulatory agencies, including the FDA, the UK’s MHRA, Japan's PMDA, and China’s NMPA.

With continued innovation in and adoption of our biosimulation software, technology, and services, we believe more life science companies worldwide will leverage more of our end-to-end platform to reduce cost, accelerate speed to market, and ensure safety and efficacy of medicines for all patients.

Key Factors Affecting Our Performance

We believe that the growth of and future success of our business depends on many factors. While each of these factors presents significant opportunities for our business, they also pose important challenges that we must successfully address to sustain our growth and improve results of operations.

Customer Retention and Expansion

Our future operating results depend, in part, on our ability to successfully enter new markets, increase our customer base, and retain and expand our relationships with existing customers. We monitor two key performance indicators to evaluate retention and expansion: new bookings and net retention rates.

57

Table of Contents

•Bookings: Our new bookings represent the estimated contract value of a signed contract or purchase order where there is sufficient or reasonable certainty about the customer’s ability and intent to fund and commence the software and/or services. Bookings vary from period to period depending on numerous factors, including the overall health of the biopharmaceutical industry, regulatory developments, industry consolidation, and sales performance. Bookings have varied and will continue to vary significantly from quarter to quarter and from year to year. See “Risk Factors — Risks Related to Our Business — Our bookings might not accurately predict our future revenue, and we might not realize all or any part of the anticipated revenue reflected in our backlog.”

•Net Retention Rates: Our net retention rates measure the percentage of recurring revenue that is retained from existing software customers over a specific period of time, inclusive of price increases and expansion, excluding revenue from acquisitions occurred within the past 12 months.

The tables below summarize our quarterly bookings and net software retention rate trends:

[[GREPCENT_TABLE]]
[["","Bookings"],["","Q1","","Q2","","Q3","","Q4","","FULL YEAR"],["","(in millions)"],["2025","$","118.2","","","$","112.0","","","$","96.6","","","$","155.3","","","$","482.1"],["2024","$","105.8","","","$","98.9","","","$","96.1","","","$","144.5","","","$","445.3"],["2023","$","112.7","","","$","85.9","","","$","84.8","","","$","118.9","","","$","402.3"],["","Net Retention Rates"],["","Q1","","Q2","","Q3","","Q4","","FULL YEAR"],["","(in percentage)"],["2025","102.4","%","","107.6","%","","103.9","%","","107.2","%","","105.3","%"],["2024","114.1","%","","108.0","%","","107.6","%","","105.5","%","","108.8","%"],["2023","108.3","%","","110.5","%","","106.4","%","","103.4","%","","108.4","%"]]
[[/GREPCENT_TABLE]]

Investments in Growth

We have invested and intend to continue to invest in expanding the breadth and depth of our solutions, including through acquisitions and international expansion. We expect to continue to invest in (i) scientific talent to expand our ability to deliver solutions across the drug development spectrum; (ii) sales and marketing to promote our solutions to new and existing customers and in existing and expanded geographies; (iii) research and development to support existing solutions and innovate new technology; (iv) other operational and administrative functions to support our expected growth; and (v) complementary business. We expect that our headcount will increase over time and also expect our total operating expenses will continue to increase over time.

Our Operating Environment

The acceptance of model-informed biopharmaceutical discovery and development by regulatory authorities affects the demand for our products and services. Support for the use of biosimulation in discovery and development from regulatory bodies, such as the FDA and EMA, has been critical to its rapid adoption by the biopharmaceutical industry. There has been a steady increase in the recognition by regulatory and academic institutions of the role that modeling and simulation can play in the biopharmaceutical development and approval process, as demonstrated by new regulations and guidance documents describing and encouraging the use of modeling and simulation in the biopharmaceutical discovery, development, testing, and approval process,

58

Table of Contents

which has directly led to an increase in the demand for our services. Changes in government or regulatory policy, or a reversal in the trend toward increasing the acceptance of and reliance upon in silico data in the drug approval process, could decrease the demand for our products and services or lead regulatory authorities to cease use of, or recommend against the use of, our products and services.

Governmental agencies throughout the world, but particularly in the United States where the majority of our customers are based

[Excerpt truncated for page length; the complete text is on the linked full-MD&A page.]

Read the full FY 2025 MD&A: /company/CERT/mda/fy2025/
All MD&A years: /company/CERT/mda/


## MD&A history

Prior-year 10-K MD&A spans are extracted from SEC filings with the same bounded parser used for the latest filing. Each year's full verbatim text is on its own sub-page.

- [FY 2024 MD&A](/company/CERT/mda/fy2024/): filed 2025-02-26; accession 0001827090-25-000014 (https://www.sec.gov/Archives/edgar/data/1827090/000182709025000014/cert-20241231.htm)
- [FY 2023 MD&A](/company/CERT/mda/fy2023/): filed 2024-02-29; accession 0001827090-24-000006 (https://www.sec.gov/Archives/edgar/data/1827090/000182709024000006/cert-20231231.htm)
- [FY 2022 MD&A](/company/CERT/mda/fy2022/): filed 2023-03-01; accession 0001558370-23-002605 (https://www.sec.gov/Archives/edgar/data/1827090/000155837023002605/cert-20221231x10k.htm)
- [FY 2021 MD&A](/company/CERT/mda/fy2021/): filed 2022-03-01; accession 0001558370-22-002608 (https://www.sec.gov/Archives/edgar/data/1827090/000155837022002608/cert-20211231x10k.htm)




## Macro cross-references

Indicators mapped to this company's SIC classification (industry 7372 Services-Prepackaged Software) by grepcent's deterministic macro-sector crosswalk. A navigational mapping, not a statistical or causal claim.

- [PAYEMS](/indicator/PAYEMS/): All Employees, Total Nonfarm
- [CES0500000003](/indicator/CES0500000003/): Average Hourly Earnings of All Employees, Total Private
- [DGS10](/indicator/DGS10/): Market Yield on U.S. Treasury Securities at 10-Year Constant Maturity

Macro-to-micro threads including this sector: [US labor market](/thread/us-labor-market/), [Growth & output](/thread/growth-output/), [Government finances](/thread/government-finances/), [Sector employment](/thread/sector-employment/).

All macro indicators: /indicators/


## For LLMs & downloads

Markdown twin: /company/CERT.md · JSON record: /company/CERT.json · verified financials: /company/CERT/financials.json / /company/CERT/financials.csv · machine TOC for the whole site: /llms.txt