A PK Mystery Solved

Challenge: A promising new drug formulation for a very rare disease failed to prove bioequivalent to a previously approved formulation. To achieve regulatory approval, the sponsor must demonstrate complete understanding of the drug’s unusual pharmacokinetics (PK) and build a sound rationale for dosing in children and adults based on small trials.

Solution: Using physiologically relevant modeling and simulation, the sponsor and Certara consultants uncovered an extensive first-pass metabolism that explained the drug's unusual PK. To optimize dosing for pediatric patients, the team modeled exposures based on body surface area. Dose simulations using that model reliably reproduced observed exposure levels and identified optimal dose strategies across age groups.

Benefits: As part of the fast-track New Drug Application for the orphan drug, the model-based analyses provided compelling evidence that the sponsor thoroughly understood the dose-concentration profile and had established safe dosing recommendations for adults and children. The FDA approved the new drug for use in patients from two years of age through adulthood.

How modeling and simulation clarified complex exposure levels and an orphan drug got approved

For orphan drugs targeting rare diseases, few patients are available for clinical study. All data collected become crucial to understanding the benefit-risk profile of a potential therapy. Model-based analyses organize molecular, pre-clinical, clinical, and competitor data into a cohesive framework that reveals a story about a molecule, from dose and exposure to benefit and safety. Through Monte Carlo simulations, that model can forecast benefit-risk outcomes for new doses or patient demographics—providing valuable insights, especially in difficult-to-study patient populations.

This model-based paradigm becomes a continuum for informing decisions at all phases of a drug development program. The field of pharmacometrics uses mathematical and statistical tools from pharmacokinetics (PK) and pharmacodynamics (PD) to combine available information on a study drug, disease, and patient population from the literature, competitors, expert knowledge and clinical trials. The resulting model describes a study drug’s exposure and benefit, including relevant uncertainties. This knowledge framework provides a thorough and quantitative basis for development decisions. It also serves as a platform for earlier and more informative regulatory communication.

Regulators expect to see pharmacometric analyses included in submissions, and apply modeling and simulation themselves to evaluate labeling and approval decisions—especially for cases that are difficult or impossible to study directly in clinical trials. Advanced modeling approaches enhance understanding of the full dose-exposure-response relationship. They provide critical insights where data are limited or noncompartmental analysis (NCA) results fall short, as may happen with orphan drugs or unusually complex PKPD profiles.

Case study – treating a rare metabolic disease

A new drug formulation represented a promising therapeutic advance for a cluster of rare diseases targeting an essential metabolic pathway. Untreated, patients with these genetic conditions face the risk of brain damage, coma and even death.

A single supportive treatment for these patients had been approved, but, while the treatment was a breakthrough, it was administered in an undesirable manner. The drug sponsor began to develop a new formulation that could reduce these administration issues.

Though urgent, development of the new treatment faced steep challenges. As very rare conditions with a high mortality rate, these "ultra orphan" disorders affect as few as 1,000 patients in the U.S. Such a small patient pool makes it challenging to obtain sufficient descriptive data from clinical trials to inform the exposure-response relationship. It is very difficult to define the compelling benefit-risk profile necessary to support a new drug filing with the U.S. Food and Drug Administration (FDA) or other regulatory agencies.  

When NCA isn't enough

The new formulation was expected to prove bioequivalent to the approved one, aiding approval with fewer clinical trials. However, mole-equivalent doses of the two drugs—that is, doses providing the same amount of active ingredient, mole-for-mole—failed to show bioequivalence in terms of plasma levels of key metabolites. In contrast, urinary metabolite excretion was almost identical between formulations. 

What was happening in the blood? Despite equivalent urinary excretion after mole-equivalent doses of the two drugs, systemic exposure to the active metabolite was lower for the new formulation. The dose-concentration disconnect was present across patient characteristics—in adults and children, healthy volunteers, patients and those with cirrhosis.

NCA provided descriptive support for the observed differences in dose, concentration, and urinary recovery of dose, but were not able to adequately describe the dose-exposure relationship of the new formulation. NCA did not permit full characterization of the drugs’ behavior and, specifically, did not answer two questions: (a) what accounted for the differences in the two drugs' plasma PK profiles despite the virtually identical excretion of the metabolite in urine, and (b) would dosing of the new drug result in differing plasma exposure to various metabolites? Regulators were unconvinced that the new drug's actions in the body were fully understood.  The drug sponsor undertook compartmental modeling to establish a more complete understanding of drug exposure.

Assessing exposure when complex PK exists

The drug sponsor contacted Certara’s Pharsight Consulting Services to take a closer look at PK and perform model-based analyses to complement the NCA. A team of sponsor scientists and Certara consultants applied mechanistic, physiologically-relevant modeling techniques to describe the blood and urine levels of key metabolites.

The analyses suggested a slower release for the new formulation, compared to the approved one. The results also supported the idea that an extended first-pass effect could explain the discrepancy between administered dose of the new drug and plasma and urinary metabolite levels. By using the urine data as an anchor to close the mass-balance loop between dose and elimination, the model enabled the team to infer what was happening to the parent and metabolites pre-systemically.

The model and the story it told fit the available data well: during its slow absorption across the intestinal lining and into the portal vein, the new drug had time to react with enzymes on its way into the body—before it reached the systemic circulation. As a result, measurements of the active metabolite in the blood were misleading; its metabolism had already happened, pre-systemically. The model quantified the pre-systemic and systemic disposition of both formulations well and provided information on the variability among patients of different ages. The semi-mechanistic model developed by Certara’s Pharsight consultants reliably described parent and metabolite measurements over time following treatment with either drug. The model was now well-positioned for use in simulations to understand the impact of dose regimen.

Extension to pediatric patients

Certara’s consultants and sponsor scientists presented the new model to the FDA, successfully demonstrating their understanding of drug exposure for the new formulation, as well as improved understanding for the already approved drug. The agency moved the conversation forward with a challenge: How would the team demonstrate appropriate exposure levels across age groups, especially in children, given that the new formulation was not bioequivalent to the other in terms of parent compound?

Certara’s consultants used the modeling work in adult patients as a framework to understand pediatric data, which showed altered exposure per body weight in children compared to adults. Literature for previously-approved drugs hinted that body surface area might provide a more useful basis than body weight for scaling. Since the developed model accounted for body size differences between patients of different ages, Certara’s consultants compared dose simulations with dosage based on body weight or body surface area. Body surface area provided better predictions of exposure per dosage than body weight, and explained all significant age-related variation in the clinical data.

A single model incorporating body surface area was able to explain variability in drug exposure for patients across adult and pediatric age groups. This model provided the basis for dosing simulations to predict exposure and evaluate dose strategies at all ages. Simulation scenarios with adult and pediatric populations played an essential role in affirming safe exposure, as well as predicting dose as a function of body surface area.

Approval across age groups

The dose simulations were provided with the New Drug Application (NDA), with fast-track status. Certara’s Pharsight consultants documented the complex pharmacometric analyses in detail for the NDA and joined in a sponsor-requested 90-day meeting with the FDA, to ensure that the agency had all it needed and to answer any questions.

The model-based analyses successfully quantified the slower absorption of the new drug form and supported the sponsor's dosing recommendations in the NDA, which included addition of the main drug metabolite in urine as one of the dosing biomarkers in the product label. The model provided compelling evidence that the sponsor thoroughly understood the compound's unusual behavior and had established safe dosing recommendations for adults as well as children.

The FDA approved the new drug for use in appropriate adult and pediatric patients, two years and older. The new drug provided improved palatability, and alleviated the sodium burden of the previous dose form, opening more options to patients with these rare, life-threatening conditions.

Conclusions

Modeling and simulation results tell a story about a candidate compound, describing its behavior based on a broad pool of information sources. With increasing frequency, drug sponsors and regulators look to that story to evaluate development plans, dosing recommendations and target indications—and to make projections to situations that are difficult to study in clinical trials.

JF Marier is a Vice President and Lead Scientist at Certara USA, Inc., e-mail [email protected]. Shawne Workman is a Scientific Writer for Certara, e-mail: [email protected]. Jonathan Monteleone is Associate Director of Pharmacometrics at Alexion Pharmaceuticals, e-mail: [email protected].