Protein C concentrate pharmacokinetics—no need to fear the curve

Terms often used in clinical pharmacology—such as population pharmacokinetic (PK) models—can seem daunting to clinicians and even to many scientists. Yet, it is commendable that the authors of the article “Evaluation of pharmacokinetics of intravenous protein C concentrate in protein C deficiency: implications for treatment initiation and maintenance,” Li et al. [1], and the journal editor have embraced these concepts and accepted that these tools are especially meaningful when applied to fragile populations such as young children.

The truth is that pharmacology has always been there. It has silently shaped the field of hemostasis for decades—even if we rarely dared to call it by name. From dosing factor concentrates to interpreting anti-Xa levels, pharmacologic reasoning has been at the heart of decision making. But because terms like clearance, volume of distribution, and area under the curve were perceived as abstract or technical, pharmacology often felt far removed from the day-to-day reality of clinicians.

This divide has begun to narrow, thanks in large part to the efforts of pioneers like Dr Iorio [2], whose work has made pharmacokinetics more accessible and clinically relevant. Through the WAPPS-Hemo platform [3], Bayesian modeling became a bedside tool, enabling personalized dosing for patients with hemophilia. This represents a pivotal shift: pharmacology no longer belongs solely to the realm of academia or regulatory agencies—it belongs in clinical conversations.

Terms like C_max (maximum concentration), C_min (trough level), and area under the curve, once buried in drug labels and regulatory documents, are now part of the clinical toolkit. A case in point is the pediatric adoption of direct oral anticoagulants (DOACs). While rivaroxaban has been prescribed at fixed doses in adults with little attention to plasma levels, its pediatric formulation was guided by sophisticated modeling—first through physiology-based PK models, then refined by population PK studies. This two-step framework exemplifies the power of pharmacologic modeling to guide dosing decisions [4]. Even though associations between drug levels and clinical outcomes may be weak or variable, the use of modeling and simulation provides structure and transparency to dosing strategies—particularly for high-risk or vulnerable patients. And yet, fear remains: fear of unfamiliar terms, curves, math, and modeling.

Even well-established therapies like unfractionated and low molecular weight heparin continue to be explored through a pharmacologic lens [5]. C_min and C_max have long informed factor (F) VIII and FIX concentrate dosing. Anti-Xa levels are an accepted proxy for heparin efficacy. But paradoxically, while these concepts are widely accepted, explicit pharmacologic reasoning is often still met with discomfort. For example, suggesting that PK modeling could tailor elective anticoagulation interruption is more likely to be met with skepticism than curiosity.

One reason may be that drug monitoring practices in thrombosis and hemostasis have evolved largely within the silo of the hemostasis laboratory. These practices—coagulometric assays such as activated partial thromboplastin time for heparin and prothrombin time for warfarin—have provided immense clinical value, but they have often operated independently of broader pharmacologic frameworks. Warfarin management, for example, requires navigating a complex interplay of pharmacokinetics, pharmacogenetics, vitamin K metabolism, and vitamin K-dependent factor dynamics—yet this intricacy is rarely acknowledged in clinical routines. Few recognize that warfarin’s PK-pharmacodynamic model in children, applicated by Hamberg et al. [6] in 2014, remains one of the best examples of successful PK-pharmacodynamic modeling in pharmacologic field. This model elegantly links S-warfarin concentration, International Normalized Ratio response, age, and pharmacogenetics—serving as a blueprint for individualized dosing algorithms.

In contrast to other medical disciplines that rely on monitoring direct plasma drug levels (eg, oncology, infectious diseases), thrombosis care has often favored more familiar, though sometimes more interference-prone, alternatives. Chromogenic anti-Xa assays are preferred for DOAC monitoring—even though liquid chromatography–tandem mass spectrometry can provide more reliable quantification in some situations such as with capillary blood specimens and samples drawn from heparinized central lines. Similarly, while thromboelastography has been used as a tool to monitor platelet inhibition, particularly with antiplatelet therapies such as aspirin and P2Y₁₂ inhibitors, its pharmacological interpretation remains underutilized and not well integrated into routine practice [7,8].

With the expanded use of DOACs and nonfactor therapies in hemophilia, the siloed approach is beginning to show its limits. There is an opportunity—indeed, a need—for stronger collaboration between hemostasis laboratories and clinical pharmacology units. Working together, we can combine traditional coagulation assays that have great utility by offering pharmacodynamic measurements with modeling and pharmacological concepts to enhance therapeutic drug monitoring. This collaborative approach could expand options for individualized care and improve patient outcomes.

This brings us back to the article by Li et al. [1], who took on the hard task of modeling intravenous protein C (PC) concentrate. This endeavor is particularly challenging due to the rarity of severe PC deficiency, variability in endogenous production, and lack of consistent drug-level data. Nevertheless, the authors succeeded in developing a sound population PK model that identifies relevant covariates and enables simulations to support clinical decision making.

Although not explicitly stated, their simulations suggest that a loading dose of 120 IU/kg may be essential for achieving therapeutic concentrations quickly—particularly in symptomatic patients. In younger children (aged < 2 years), maintenance dosing every 6 hours seems optimal, while older children may be managed with less frequent dosing to avoid supratherapeutic PC levels. These insights, even if preliminary, are of clear clinical value.

Treating patients with congenital PC deficiency using PC concentrate represents a significant financial and clinical burden. Modeling efforts such as this offer a practical, rational, and evidence-informed way to optimize therapy. Many patients continue to receive subcutaneous PC based on International Society on Thrombosis and Haemostasis recommendations [9], but studies like this using that route of administration are still missing. Research and expansion of clinical registries that include PC levels and outcomes in the most diverse scenarios are crucial to continue to gather pharmacological information to guide clinicians to take more appropriate decisions.

Despite data limitations, the authors of this article have taken a brave and scientifically grounded step forward. They have resisted the urge to overstate their findings, instead offering a transparent analysis that allows readers to apply these insights judiciously. This kind of work should be celebrated—it pushes the field forward not just through its findings, but through its methodology and collaborative ethos.

So, to clinicians and readers who may still be wary: don’t fear the curve. You’ve been using pharmacologic concepts all along—now it’s time to name them, embrace them, and partner with your colleagues in pharmacology and laboratory medicine. Together, we can elevate therapeutic decision making in thrombosis and hemostasis, one dose at a time.