The dearth of treatments for rare diseases represents a huge unmet medical need. Rare disease drug development faces clinical, regulatory and commercial challenges. Modeling and simulation elucidates the dose-concentration-effect relationship to inform development decisions. For example, pharmacokinetic (PK) modeling expedited a new drug approval for a rare disease, primary biliary cholangitis (PBC).

PBC causes impaired bile flow from the liver. Elevated bile acid concentrations injure hepatocytes and eventually lead to liver failure and death. The only currently approved treatment for PBC was ursodeoxycholic acid (UDCA). However, not all patients respond to UDCA.

Intercept Pharmaceuticals sought to develop obeticholic acid (OCA) as an alternative treatment. OCA decreases bile acids concentrations and reduces hepatocellular injury. Because disease progression causes liver damage, the Intercept team needed to develop a dosing strategy for patients with and without hepatic impairment. A clinical study was conducted wherein healthy volunteers and patients with hepatic impairment were treated with OCA. Study results revealed that systemic exposure of OCA failed to correspond to its effects in the liver. A robust dosing strategy required understanding the relationship between systemic and hepatic OCA exposure.

Certara Strategic Consulting scientists used Phoenix NLME to perform mechanistic PK modeling. The model predicted OCA-plasma exposures comparable to observed exposures in healthy volunteers and patients with hepatic impairment. Both the model and clinical data showed elevated systemic, but not liver, exposure of OCA in patients with hepatic impairment. The modeling and clinical trial results supported the safety and efficacy of the dosing strategy.

In May 2016, the FDA approved Ocaliva (obeticholic acid)― the first new drug for PBC in almost 20 years. The case of Ocaliva demonstrates how sponsors can accelerate drug approvals through leveraging PK modeling.