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Intravenous immunoglobulins (IVIg) are effective for treating chronic inflammatory demyelinating polyneuropathy (CIDP), although treatment needs are variable and need to be individualized. Dose and frequency requirements are not currently predictable in advance. In Guillain-Barré syndrome, IVIg interpatient pharmacokinetic variations have been demonstrated in relation to clinical outcome. We studied 15 patients with CIDP following two routine courses of IVIg. IgG levels were assessed pretreatment and 14 days post-treatment. Best clinical response (BCR) was ascertained in each case, predefined, according to individual patients' circumstances, on the 10 m walk, or MRC sum score, or Jamar grip dynamometry. Correlations between IgG level variations, doses administered, weight, body mass index, BCR and infusion interval were determined. Postinfusion rise in IgG levels were correlated in individual patients (p = 0.005), but interpatient variability was high. No correlations were ascertained between IgG level variation and weight, body mass index, BCR, total dose of IVIg administered, or dose of IVIg administered per kilogram per week. There were significant correlations between total dose administered and post-infusion IgG level at 14 days (p = 0.004) and between infusion interval and mean rise in IgG level (p = 0.001) These findings suggest significant variability in IgG metabolism between patients, unrelated to minimal effective dose administered, weight, body mass index or degree of functional improvement. Required frequency of IVIg infusions may, however, importantly relate to patient-specific post-infusion rise in IgG levels hence possibly explaining inter-patient differences in treatment frequency needs. IgG level monitoring may be helpful in establishing optimum treatment regimens in individual cases.

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Previous methods of veri cation tend to keep correctness, timing and performance separate. In this paper we present a process algebra based methodology for the integrated m o delling and veri cation of correctness, performance and timing properties of concurrent systems. We have applied the method to the domain of asynchronous hardware and used an asynchronous micropipeline as an illustrative example.