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R e s u l t s ( c o n t i n u e d )

The Relationship Between Two Insulin Assays Used to Determine Bioequivalence and Dose Proportionality of AFREZZA® Insulin Administered Using a Gen2 Inhaler

Compared to a MedTone® Inhaler: Simulation of Clinical Trials and Actual Data

Mark T. Marino, MD and James P. Cassidy, MS MannKind Corporation, Valencia, California

Objective: MannKind Corporation has conducted Phase 3 studies with AFREZZA® insulin using the MedTone® Inhaler. The Gen2 Inhaler is designed to be smaller, easier to use, and require less inspiratory effort and fewer inhalations. A bioequivalence (BE) trial was conducted and insulin con-centrations quantified using the Roche ECLIA which is highly sensitive and capable of quantifying insulin over a very wide range of concentrations without dilutions. An RIA method that was fully consistent with the FDA guidelines was subse-quently used on the same serum samples.

Method: Bioequivalence samples that were measured by the Roche ECLIA method were analyzed for bioequivalence. Using published data on the linear relationship and error (CV%) between the Roche ECLIA and a RIA method, 1000 bioequivalence trials were simulated. RIA analysis was then done and the results were analyzed for bioequivalence.

Results: The results for the bioequivalence analysis using the Roche ECLIA assay demonstrated BE for all groups (20 U Gen2 vs. 30 U MedTone and 2 x 10 U Gen2 and 20 U Gen2). The simulations showed all BE trials using the published error (4.5 % CV) passed and only 22 out of 1000 simulated trials failed using a higher than published error (10% CV). The samples that were subsequently ana-lyzed by an RIA method also demonstrated bioequivalence but with larger confidence intervals.

Conclusion: The conclusions of the bioequivalence trial were not substantially changed in the simulations. The simu-lations demonstrated that by reanalyzing the samples with an assay of higher variability the conclusion of the trial did not change but it was shown that the assays with a higher CV% were more likely to result in a type I error. This was confirmed by the actual reanalysis using the RIA assay.

A b s t r a c t

Bioequivalence criteria are based upon a statistical analy-sis of the derived parameters log (AUC) and log (Cmax). In general, when the 90% confidence interval for the AUC and Cmax of the new, or innovator, product (Gen2) falls within 80% to 125% of the point estimate of the old, or reference, product (MedTone), the bioequivalence is considered to be established. This allows for the new product to be consid-ered equal to the old product (i.e., “orange book” equiva-lence for generic prescriptions) and also allows all safety and efficacy data from the old product to be extrapolated to the new product.

I n t r o d u c t i o n ( c o n t i n u e d )

Primary Objective:To determine if the ECLIA assay method and RIA assay method provide similar results in regards to insulin levels, variability, and bioequivalence.

Secondary Objective:To determine if the Monte-Carlo simulations were predictive of the actual RIA assay results in regards to bioequivalence.

S t u d y O b j e c t i v e s

Plasma samples used in the bioequivalence study (MKC-TI-142) were analyzed for insulin concentration using both the ECLIA and RIA methods.

S t u d y D e s i g n

Prior to reanalysis of the serum samples from MKC-TI-142 using the RIA methodology, data was simulated to deter-mine if this more variable assay would affect the bioequiva-lence calculations. Simulations were run using the insulin concentration data obtained from the ECLIA analysis and adding an additional 4.5% variability reported for the RIA methodology. The PK results obtained after 1000 simula-tions of insulin concentration vs. time curves with the added RIA variability are shown in Figure 1.

Figure 2 shows the actual correlation of serum insulin con-centrations from the study (N=1914 samples) analyzed by the ECLIA and RIA methodologies. The mean C-peptide corrected insulin concentration obtained from analysis using the ECLIA and RIA methodologies are shown in Figures 3 and 4, respectively.

R e s u l t sMannKind Corporation has conducted a clinical develop-ment program with AFREZZA insulin (Technosphere® Insulin [TI] Inhalation Powder) for the treatment of patients with type 1 and type 2 diabetes mellitus. The AFREZZA Inhala-tion System consists of AFREZZA insulin and the MedTone Inhaler device. AFREZZA insulin is a pulmonary delivered inhaled insulin formulation containing human insulin ad-sorbed onto Technosphere® particles. Technosphere® par-ticles, microparticles formed from fumaryl diketopiperazine (FDKP), have a median diameter of 2 to 2.5 microns. The particles can carry insulin to the lung where they are ab-sorbed into the systemic circulation. The MedTone Inhaler is a palm sized, reusable, dry powder, breath-powered, high resistance, low flow inhalation device that uses the energy of a subject’s inspiratory flow to deagglomerate and aerosolize the AFREZZA inhalation powder.1

As part of the MannKind next generation device develop-ment program, the Gen2 Inhaler was developed. This device is designed to be smaller, easier to load and handle, and needs less inspiratory flow pressure and duration as well as cartridge load to deliver the same dosage of insulin as from the current MedTone Inhaler. A bioequivalence trial was run between the MedTone and Gen2 Inhalers using an ECLIA to measure insulin concentrations. While the assay is the most sensitive and specific assay available for the determination of insulin, it did not have samples for a standard curve actu-ally “run” with each analytical run, but rather used a manu-facturer supplied equation (Rodbard) to convert detector signal to concentration where the equation is adjusted daily by the use of calibrators provided with each reagent lot. Prior to running the RIA, a series of Monte-Carlo simulations were run using the published relationship between the two assays assuming a random error model. Subsequently a RIA method, which is less sensitive and specific, was run using the same plasma samples and the data from those assays were also used to assess bioequivalence.

I n t r o d u c t i o n

Based upon the simulated insulin vs. time concen-tration values, the AUC and Cmax values were deter-mined for each of the 46 individuals included in the primary BE analysis (based upon the SAP-specified inclusion criteria for PK analysis).

All parameters and dose groups (20 U Gen2 vs. 30 U MedTone and 2 x 10 U Gen2 vs. 20 U Gen2) passed the BE criteria. As the statistical technique used in this report to analyze these values assumed a 2 x 2 study design, the confidence intervals are more conservative than that used to determine BE

pooling the variance from all 3 doses. The BE evalu-ation for the higher variability (10%, data not pre-sented here) assay assumptions also meets the BE criteria in the majority of cases (2 simulations failed on the lower CI in the 2 x 10 U Gen2 vs. 20 U Gen2 group and 22 simulations failed on the upper CI in the 20 U Gen2 vs. 30 U MedTone group).

The results of the 1000 simulations show that the effect of using an assay with higher variability is on the confidence intervals — which are widened and

not centered around the estimated confidence lim-its from the original study — as expected.

Despite this, the predictions were that running a more variable RIA assay on the same samples mea-sured by the Roche ECLIA assay — while increas-ing the size of the 90% CI — would still confirm BE. When the samples were actually analyzed by the RIA methodology, the BE results matched the pre-dictions of still being bioequivalent while the 90% confidence interval was slightly wider.

C o n c l u s i o n s

Diabetes Technology Meeting ~ November 11-13, 2010 ~ Bethesda, MDContact: Mark T. Marino ~ 201.983.5238 ~ mmarino@mannkindcorp.comMannKind Corporation ~ 61 South Paramus Road ~ Paramus, NJ 07652

AUC 10 U vs 20 U CPEP

Cmax 10 U vs 20 U CPEP

AUC 30 U vs 30 U CPEP

Cmax 20 U vs 30 U CPEP

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C-peptide corrected insulin (CPEP) AUC and Cmax calculated from 1000 simulated insulin con-centration vs. time curves using the original ECLIA data and add-ing the additional 4.5% variability for the RIA assay. The 90% con-fidence intervals with the 80% and 125% bioequivalence limits are included.

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Multiple R–squared: 0.8962, Adjusted R–squared: 0.8961F–statistic: 1.649e+04 on 1 and 1911 DF, p value: <2.2e–16

Mean with 95% CI (black), Prediction Interval (Fitted Value ± 2 SD) (red),and 95% Confidence Ellipse (blue)

Correlation, prediction limits, and confidence limits between the ECLIA and RIA assays.

Figure 2

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Summary of C-peptide corrected insulin concentrations (MKC-TI-142) using the ECLIA assay (mean ± SE).

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Summary of C-peptide corrected insulin concentrations (MKC-TI-142) using the RIA assay (mean ± SE).

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