Optimize Dosing of Anti-TNF Biologics in Ulcerative Colitis
Optimize Dosing of Anti-TNF Biologics in Ulcerative Colitis
Accelerated clearance of anti-TNF biologics in children and adults with ASUC may explain high treatment failure rates with conventional weight-based dosing developed for treatment of ambulatory patients with moderate to severely active disease. Alternative dosing regimens that ensure sustained optimal biologic exposure, especially early in the treatment of ASUC when inflammatory burden and colon injury is highest, may lead to improved outcomes. As a quality improvement intervention, Gibson et al. introduced an 'accelerated' infliximab induction regimen for the treatment of ASUC. In this regimen, subsequent induction doses of infliximab (5 mg/kg) were administered based on worsening clinical symptoms or inflammatory markers, instead of the standard regimen of doses at 0, 2 and 6 weeks. The rate of early colectomy was 6.7% in patients treated with the accelerated induction regimen, compared with 40% in a group of similar historical controls treated with the standard induction regimen; although, long-term colectomy rates were similar between the two groups. While this study serves as an important proof of principal that alternative dosing regimens may be needed in patients with ASUC, doses were still administered in a reactive fashion in response to deteriorating clinical signs.
Given the clear association between serum levels of anti-TNF biologics and patient outcomes, it would seem rational to monitor levels at specified time points and adjust doses to achieve optimal cut-off levels. This therapeutic monitoring approach is being actively investigated in patients with moderate to severely active UC and CD based mainly on post-induction levels obtained at 6–14 weeks associated with improved outcomes. However, time is of the essence in patients with ASUC, and measurement of serum drug levels after induction will not be helpful for the 25–30% of ASUC patients who will undergo colectomy in the first 2–4 weeks after treatment. Therefore, there is a need to develop approaches to optimise anti-TNF dosing at the outset of treatment for ASUC.
We hypothesise such optimised anti-TNF regimens for ASUC will be achieved by individualised dosing and proactive adjustment based on early measurement of levels and biomarkers of response. At this time, however, optimal time points and targets for early anti-TNF levels (i.e. within the first week of treatment) are unknown. The largest anti-TNF PK–PD studies from UC clinical trials have analysed primarily trough and peak blood samples with each infusion, with no additional early measurements between the first two infusions. Therefore, we propose that the first step towards developing optimised dosing strategies in ASUC will be to assemble a cohort of anti-TNF-naïve patients with steroid-refractory ASUC being initiated on an anti-TNF biologic to assess the following: (i) individual baseline patient and disease parameters hypothesised to predict PK, (ii) serial measurements of anti-TNF levels within the first week of treatment and (iii) measures of early clinical response and longer term clinical remission. With such data, one could determine whether variability in early anti-TNF exposure and clearance influences initial clinical response, and generate a predictive model that relates anti-TNF PK back to clinically relevant baseline parameters (e.g. dose, weight, albumin, TNF, inflammatory markers, etc.).
Looking towards the future, software decisions support tools or 'dashboards' that incorporate a predictive PK model may be tested to tailor anti-TNF dosing regimens to individual patients with ASUC, and reduce the variability in effective drug exposure. Dashboard systems can incorporate baseline covariates into a PK model to reduce unexplained variability, and propose a dosing regimen estimated to result in optimal drug exposure for a given patient. As proof of this principle, in adult patients with UC and CD of varying severity, the incorporation of individual weight and albumin parameters increased the accuracy of predicted serum infliximab concentrations. Once the individualised dosing regimen is applied, early proactive monitoring of serum drug concentrations and biomarkers of treatment response (e.g. CRP) can be used to update the PK model and guide subsequent dosing in real time (adaptive dosing). Patients with ASUC are an ideal population for the clinical application of therapeutic dashboards since they likely have profound inter-individual variability in anti-TNF PK, and the severity of their condition requires early proactive effective dosing. The future development and clinical application of PK modelling in the form of dashboards that account for TNF burden (the Sponge), inflammation-induced RES activation (the Shark) and intestinal losses (the Sieve), will likely result in sustained exposure to the drug, mucosal healing and fewer colectomies in children and adults with ASUC.
The Future of Anti-TNF Therapy for ASUC
Accelerated clearance of anti-TNF biologics in children and adults with ASUC may explain high treatment failure rates with conventional weight-based dosing developed for treatment of ambulatory patients with moderate to severely active disease. Alternative dosing regimens that ensure sustained optimal biologic exposure, especially early in the treatment of ASUC when inflammatory burden and colon injury is highest, may lead to improved outcomes. As a quality improvement intervention, Gibson et al. introduced an 'accelerated' infliximab induction regimen for the treatment of ASUC. In this regimen, subsequent induction doses of infliximab (5 mg/kg) were administered based on worsening clinical symptoms or inflammatory markers, instead of the standard regimen of doses at 0, 2 and 6 weeks. The rate of early colectomy was 6.7% in patients treated with the accelerated induction regimen, compared with 40% in a group of similar historical controls treated with the standard induction regimen; although, long-term colectomy rates were similar between the two groups. While this study serves as an important proof of principal that alternative dosing regimens may be needed in patients with ASUC, doses were still administered in a reactive fashion in response to deteriorating clinical signs.
Given the clear association between serum levels of anti-TNF biologics and patient outcomes, it would seem rational to monitor levels at specified time points and adjust doses to achieve optimal cut-off levels. This therapeutic monitoring approach is being actively investigated in patients with moderate to severely active UC and CD based mainly on post-induction levels obtained at 6–14 weeks associated with improved outcomes. However, time is of the essence in patients with ASUC, and measurement of serum drug levels after induction will not be helpful for the 25–30% of ASUC patients who will undergo colectomy in the first 2–4 weeks after treatment. Therefore, there is a need to develop approaches to optimise anti-TNF dosing at the outset of treatment for ASUC.
We hypothesise such optimised anti-TNF regimens for ASUC will be achieved by individualised dosing and proactive adjustment based on early measurement of levels and biomarkers of response. At this time, however, optimal time points and targets for early anti-TNF levels (i.e. within the first week of treatment) are unknown. The largest anti-TNF PK–PD studies from UC clinical trials have analysed primarily trough and peak blood samples with each infusion, with no additional early measurements between the first two infusions. Therefore, we propose that the first step towards developing optimised dosing strategies in ASUC will be to assemble a cohort of anti-TNF-naïve patients with steroid-refractory ASUC being initiated on an anti-TNF biologic to assess the following: (i) individual baseline patient and disease parameters hypothesised to predict PK, (ii) serial measurements of anti-TNF levels within the first week of treatment and (iii) measures of early clinical response and longer term clinical remission. With such data, one could determine whether variability in early anti-TNF exposure and clearance influences initial clinical response, and generate a predictive model that relates anti-TNF PK back to clinically relevant baseline parameters (e.g. dose, weight, albumin, TNF, inflammatory markers, etc.).
Looking towards the future, software decisions support tools or 'dashboards' that incorporate a predictive PK model may be tested to tailor anti-TNF dosing regimens to individual patients with ASUC, and reduce the variability in effective drug exposure. Dashboard systems can incorporate baseline covariates into a PK model to reduce unexplained variability, and propose a dosing regimen estimated to result in optimal drug exposure for a given patient. As proof of this principle, in adult patients with UC and CD of varying severity, the incorporation of individual weight and albumin parameters increased the accuracy of predicted serum infliximab concentrations. Once the individualised dosing regimen is applied, early proactive monitoring of serum drug concentrations and biomarkers of treatment response (e.g. CRP) can be used to update the PK model and guide subsequent dosing in real time (adaptive dosing). Patients with ASUC are an ideal population for the clinical application of therapeutic dashboards since they likely have profound inter-individual variability in anti-TNF PK, and the severity of their condition requires early proactive effective dosing. The future development and clinical application of PK modelling in the form of dashboards that account for TNF burden (the Sponge), inflammation-induced RES activation (the Shark) and intestinal losses (the Sieve), will likely result in sustained exposure to the drug, mucosal healing and fewer colectomies in children and adults with ASUC.