OP21 Positivity thresholds of total infliximab and adalimumab anti-drug antibody assay: The prevalence of clearing and transient anti-drug antibodies in a national therapeutic drug monitoring service
Bibliographic record
Abstract
Abstract Background Anti-drug antibodies can affect biopharmaceutical pharmacokinetics by increasing or decreasing drug clearance. Drug-tolerant (total), unlike drug-sensitive (free), antibody assays permit antibodies to be measured in the presence of a drug. We sought to confirm the positivity threshold of our total anti-tumour necrosis factor (TNF) antibody ELISA assays in a sample of healthy volunteers and to use this threshold to report the prevalence of clearing and transient antibodies in patients treated with infliximab and adalimumab. Methods Serum was obtained from a random sample of 498 anti-TNF-naïve healthy adults recruited to the Exeter Ten Thousand study and tested for total anti-drug antibodies to infliximab and adalimumab. Using recommendations for confirmatory anti-drug antibody validation, we used bootstrapping to calculate the 80% one-sided lower confidence interval [CI] of the 99th centile to define assay thresholds. We used paired drug and anti-drug antibody levels derived from our national therapeutic drug monitoring service to report the distribution of clearing (antibody positive, drug negative) vs. non-clearing (antibody positive, drug positive) antibodies. In patients with at least two test results, antibodies were classified as transient (single positive test with subsequent negative test) or persistent (at least two positive tests). Results The 80% one-sided lower CI of the 99th centile titre for total anti-drug antibody to infliximab and adalimumab were 8.7 AU/ml and 5.9 AU/ml, respectively. Using the manufacturer’s recommended threshold of 10 AU/ml for both total anti-TNF antibody assays, in healthy individuals, the prevalence of positive antibodies to infliximab and adalimumab was 1% (5/498) and 0.2% (1/498), respectively. Using the manufacturer’s threshold, at the time of last testing, of 7447 and 4054 patients treated with infliximab and adalimumab; 20.9% (n = 1,554) and 8.0% (n = 326) had clearing antibodies and 26.5% (n = 1973) and 12.1% (n = 490) had non-clearing antibodies, respectively (Figure 1). Using our newly defined threshold in the same cohorts; 21.1% (n = 1573) and 8.4% (n = 339) had clearing antibodies and 28.0% (n = 2083) and 20.0% (n = 812) had non-clearing antibodies, to infliximab and adalimumab, respectively. Amongst patients with at least two tests, most developed persistent antibodies (Figure 2). Irrespective of anti-TNF drug, or threshold used, less than 10% patients developed transient antibodies. Conclusion We report lower positivity thresholds for the IDKmonitor® total anti-TNF antibody ELISA assays than the manufacturer, in particular, for adalimumab. Transient antibody formation is uncommon: most patients develop persistent anti-drug antibodies that lead to drug clearance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".