In this blog post, we’ll share six issues that are among the most common sources of regulatory skepticism.

Poor traceability or undocumented data transformations

When reviewers cannot clearly trace how the analysis dataset was derived from source data, confidence in the entire analysis is undermined. Missing documentation for data cleaning, filtering, or variable derivation creates ambiguity and prevents independent evaluation. Even minor inconsistencies, such as unexplained exclusions or time variable misalignment, can trigger extensive follow-up questions and delay review.

Lack of transparency in handling BLQ data, outliers, or missing values

Ad hoc or poorly justified approaches to data issues are a frequent source of regulatory concern. For example, excluding outliers without justification, applying inappropriate BLQ methods, or ignoring missing data mechanisms can introduce bias. Reviewers expect clear documentation of these decisions, along with sensitivity analyses demonstrating that conclusions are not driven by arbitrary choices.

Something to remember, most of these issues do not stem from what would appear to be “incorrect” modeling techniques, but from insufficient transparency and justification. In practice, reviewers may lose trust in models not because they may be wrong, but because the reviewer cannot confidently determine whether they are right.

Inadequate sensitivity analyses for key assumptions

High-impact assumptions, such as handling of BLQ data, residual error structures, extrapolation beyond the available data, or included mechanisms of action must be stress-tested. Failure to explore how alternative assumptions affect conclusions raises concerns about robustness. Sensitivity analyses are particularly important for models informing dosing or labeling decisions, where small changes can have meaningful clinical implications.

Unjustified model structure or overly complex models without added value

Models that are overly complex without clear improvement in predictive performance or interpretability raise concerns about overfitting and lack of parsimony. Similarly, structural assumptions (e.g., compartmental models, mechanistic components) must be justified based on prior knowledge or biological rationale. Without this, reviewers may question whether the model reflects true system behavior or is simply tailored to the dataset.

Inconsistent or incomplete diagnostics

Providing standard diagnostics (e.g., goodness-of-fit plots, Visual Predictive Checks, VPCs) is necessary but not sufficient. Trust is reduced when diagnostics are incomplete, poorly labeled, or inconsistent with reported conclusions. For example, claiming adequate model performance while visual predictive checks show systematic bias will immediately raise concerns. Diagnostics must not only be presented but also interpreted in a way that aligns with the overall narrative.

Over-reliance on statistical significance without clinical interpretation

Statistical criteria (e.g., p-values, likelihood ratio tests) should not be the sole basis for model decisions or interpretation of model results. As an example, covariates might be included based on statistical criteria. However, regulatory reviewers will expect covariate effects to be clinically meaningful and biologically plausible. Models that include statistically significant but clinically irrelevant covariates risk being viewed as unstable or non-generalizable, especially in extrapolation scenarios.

It is critical to understand regulatory perspectives and build your development strategy to avoid these and other potential issues around model trustworthiness. Schedule a 15-minute call with one of our regulatory experts to learn how we can support your program.

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Glyoxylic acid (GA), the active ingredient of heat-activated hair straightening products (GHSPs) has been discussed in the context of acute kidney injury (AKI) via oxalic acid (OA) crystal formation and of heat-decomposition resulting in release of formaldehyde. Assessment of dermal absorption following realistic GHSP treatments with two marketed products resulted in maximally 7.73 μg/cm² of bioavailable GA/application. Considering the scalp area of 580 cm², the systemic GA exposure of consumers was 4.48 mg, equivalent to 1.1 mg OA taking into account that 25% GA is dermally metabolized to OA. Assessment of GA exposure to stylists’ hands indicated systemic OA levels in the range of 0.026 mg/day (assuming 3 treatments in one day). Compared to typical dietary and endogenous sources of OA of 22–45 mg/day, GHSP-dependent OA exposures of consumers and stylists were 20–41-fold and > 860-fold lower, respectively. PBK prediction of GHSP-dependent renal OA excretion of consumers was <1.27 mg/day compared with normal excretion of ∼25 mg/day and the 40 mg/day threshold associated with AKI. Predicted kidney OA concentrations during GHSP exposure further indicated that OA crystal formation is unlikely to occur. Assessment of the release of the GA heat-decomposition byproduct formaldehyde in the ambient air during GHSP treatment was <25 μg/m³ and below regulatory exposure limits e.g., 100 μg/m³ (WHO indoor air quality limit). In conclusion, quantification of GA-dependent formaldehyde and OA exposure indicates no health concerns for consumers and stylists under the described realistic GHSP treatment conditions.

By Nicola J. Hewitt, Carsten Goebel, Jens Diller, Anne Fuchs, Rolf Fautz, Brunhilde Blömeke, Katharina Schwarz, Shimpei Terasaka, Kazutoshi Saito, Rebecca Justiniano, Gábor von Bölcsházy

The biocompatible macromolecules play a pivotal role in enhancing the performance of various drug delivery systems. In the current work, cellulose acetate (Opadry® CA), microcrystalline cellulose and an intrinsically uncharged polymer, polyethylene oxide (Polyox WSR N 80 and Polyox WSR 303), were evaluated for developing a bilayer push-pull osmotic tablet for dexibuprofen. The drug layer was comprised of Polyox WSR N 80, osmogen, microcrystalline cellulose and magnesium stearate. The push layer consisted of Polyox WSR 303 and pigments (Fe 2O3) in addition to osmogen and lubricant. The optimum levels of the input variables, osmogen (sodium chloride), orifice size, and percent coating weight gain were determined using the simultaneous multivariate techniques of Artificial Neural Network (ANN) and Central Composite Design (CCD) to achieve the targeted drug release profile. The ANN model’s prediction profiler was cross-validated using the CCD-optimized formulation. The tabletability of the poorly compressible drug, dexibuprofen, was improved by incorporating microcrystalline cellulose as a diluent. The ANN- and CCD-driven trial and optimized formulations were tested for both critical and pharmaceutical quality attributes. Additionally, the optimized formulations FANN was also tested for thermal and chemical stability, physicochemical interactions, and surface morphology. Physiologically Based Pharmacokinetic (PBPK) models for optimized formulations were developed using GastroPlusTM to simulate in vivo plasma profiles and compare with the real-time human pharmacokinetic data. The study demonstrates the promising role of biocompatible macromolecules in compressing the poorly compressible molecule, dexibuprofen, and modulating its release and in vivo pharmacokinetic performance from an osmotically controlled push-pull system for 12 h.

By Nazish Mumtaz, Rabia Ismail Yousuf, Muhammad Harris Shoaib, Kamran Ahmed, Muhammad Talha Saleem, Fahad Siddiqui, Sadaf Farooqi, Muhammad Suleman Imtiaz

Background
Cefotaxime (CFT) is a broad spectrum, third-generation cephalosporin antibiotic prescribed for the treatment of severe infections, yet dosing guidelines for pediatric with renal impairment is scarce. The current study aimed to develop a physiological based pharmacokinetic (PBPK) model to characterize CFT disposition and model-based recommend dose adjustments in pediatrics with renal impairment.

Methods
Initially, the PBPK model of CFT was developed in adults with normal renal function before being scaled to pediatrics, considering age-related physiological changes using GastroPlus® software. Renal impairment was modelled through optimization of tubular secretion and glomerular filtration parameters based on observed data for both adults and pediatric populations.

Results
The model reasonably reproduced the observed pharmacokinetic profiles and showed acceptable agreement with the data (fold error ranges 0.84–1.37) or with renal impairment (fold error ranges 0.87–1.12). When compared to children with normal renal function, the predicted AUC0−∞ in children with renal impairment increased to 1.22- and 1.89-fold for moderate and severe renal impairment, respectively. Model-informed dose recommendations were 60% and 48% of the standard pediatric dose for moderate and severe renal impairment, respectively.

Conclusion
This PBPK framework supports rational, model-informed dosing of CFT in pediatric patients with varying renal impairment and supports dose recommendation development for high-risk populations.

By Najia Rahim, Muhammad Sarfraz & Muhammad Wahajuddin

Third Quarter 2026 Financial Highlights (as compared to third quarter 2025)

• Total revenue increased 7% to $21.9 million
• Software revenue was flat at $12.6 million, representing 58% of total revenue
• Services revenue increased 20% to $9.3 million, representing 42% of total revenue
• Gross profit was $15.1 million and gross margin was 69%, compared to $13.0 million and 64%
• Net income of $3.6 million and diluted earnings per share of $0.18, compared to net loss of $67.3 million and diluted losses per share of $3.35
• Adjusted EBITDA of $7.9 million, representing 36% of total revenue, compared to $7.4 million, representing 37% of total revenue
• Adjusted net income of $6.1 million and adjusted diluted EPS of $0.30 compared to adjusted net income of $9.0 million and adjusted diluted EPS of $0.45

Nine Months 2026 Financial Highlights (as compared to nine months 2025)

• Total revenue increased 5% to $64.6 million
• Software revenue decreased 2% to $36.1 million, representing 56% of total revenue
• Services revenue increased 14% to $28.5 million, representing 44% of total revenue
• Gross profit was $42.2 million and gross margin was 65%, compared to $36.4 million and 59%
• Net income of $8.8 million and diluted earnings per share of $0.43, compared to net loss of $64.0 million and diluted losses per share of $3.19
• Adjusted EBITDA of $20.2 million, representing 31% of total revenue, compared to $18.5 million, representing 30% of total revenue
• Adjusted net income of $15.7 million and adjusted diluted EPS of $0.78, compared to $18.7 million and adjusted diluted EPS of $0.93

Management Commentary

“We delivered solid third quarter results, with revenue increasing 7%, highlighted by strength in our services revenue, which grew 20%, while software revenue was flat year over year,” said Shawn O’Connor, Chief Executive Officer of Simulations Plus. “Our performance reflects the resilience of our business model and the value our solutions provide to clients across the drug development lifecycle.”

“Subsequent to quarter end, on June 15, 2026, we entered into a definitive merger agreement to be acquired by affiliates of Altaris, LLC (“Altaris”). We believe the transaction better positions Simulations Plus to further advance its scientific leadership and expand the impact of our model-informed and AI-enabled solutions. As we move toward the expected closing in the fourth quarter of calendar 2026, we remain focused on delivering for our clients and executing at a high level throughout this transition.”

Non-GAAP Financial Measures

This press release contains “non-GAAP financial measures,” which are measures that either exclude or include amounts that are not excluded or included in the most directly comparable measures calculated and presented in accordance with U.S. generally accepted accounting principles (“GAAP”).

A further explanation and reconciliation of these non-GAAP financial measures is included below and in the financial tables in this release.

The Company believes that the non-GAAP financial measures presented facilitate an understanding of operating performance and provide a meaningful comparison of its results between periods. The Company’s management uses non-GAAP financial measures to, among other things, evaluate its ongoing operations in relation to historical results, for internal planning and forecasting purposes, and in the calculation of performance-based compensation. Adjusted EBITDA and Adjusted Diluted EPS represent measures that we believe are customarily used by investors and analysts to evaluate the financial performance of companies in addition to the GAAP measures that we present. Our management also believes that these measures are useful in evaluating our core operating results. However, Adjusted EBITDA and Adjusted Diluted EPS are not measures of financial performance under accounting principles generally accepted in the United States of America and should not be considered an alternative to net income, operating income, or diluted EPS as indicators of our operating performance or to net cash provided by operating activities as a measure of our liquidity. We believe the Company’s Adjusted EBITDA and Adjusted Diluted EPS measures provide information that is directly comparable to that provided by other peer companies in our industry, but other companies may calculate non-GAAP financial results differently, particularly related to nonrecurring, unusual items.

Please note that the Company has not reconciled the adjusted EBITDA or adjusted diluted earnings per share forward-looking guidance included in this press release to the most directly comparable GAAP measures because this cannot be done without unreasonable effort due to the variability and low visibility with respect to costs related to acquisitions, financings, and employee stock compensation programs, which are potential adjustments to future earnings. We expect the variability of these items to have a potentially unpredictable, and a potentially significant, impact on our future GAAP financial results.

Adjusted EBITDA

Adjusted EBITDA represents net income excluding the effect of interest expense (income), provision (benefit) for income taxes, depreciation and amortization, equity-based compensation expense, loss (gain) on currency exchange, impairment charges, change in fair value of contingent consideration, reorganization expense, acquisition and integration expense, and other items not indicative of our ongoing operating performance.

Adjusted Net Income and Adjusted Diluted EPS

Adjusted net income and adjusted diluted earnings per share exclude the effect of amortization, equity-based compensation expense, loss (gain) on currency exchange, impairment charges, change in fair value of contingent consideration, reorganization expense, acquisition and integration expense, and other items not indicative of our ongoing operating performance as well as the income tax provision adjustment for such charges.

The Company excludes the above items because they are outside of the Company’s normal operations and/or, in certain cases, are difficult to forecast accurately.

View full results here.