Enhanced Decision Making from Dissolution Automation

Harnath Doddapaneni*, John Jushchyshyn

SmithKline Beecham Pharmaceuticals Research & Development

Upper Merion, PA

*To whom to send all correspondence.

Abstract

Dissolution automation initiatives have been traditionally viewed as a resource management tool. The ability of automated dissolution to generate high quality, reproducible and correlative data has been largely overlooked. This paper will discuss long term dissolution data generated on development batches of drug product that compares manual approaches versus an automated approach. The data produced using automated methods reduce or eliminate variation due to slight changes in manual techniques which occur from analyst to analyst over a period of years in a typical stability study. While the outcome of a stability exercise is equivalent, the data produced using automated procedures allow management decision making at a much earlier stage in the stability cycle when compared to approaches which are inherently more variable.

Introduction

SmithKline Beecham Pharmaceuticals currently has a large pipeline of compounds. Development teams are challenged to progress these compounds through Phase III clinical studies in an accelerated transnational file. Development dosage units are normally evaluated on stability using dissolution profiles. An opportunity exists to review the long-term trends of automated dissolution data and its ability to predict trends at an early stage.

The data produced using automated dissolution techniques eliminate variation due to operator to operator biases in manual techniques that occur over a period of years in a typical stability study. Development teams screen large numbers of formulations. If a stability trend is observed early on, this can become a management tool for decision making long before specification limits are challenged.

Experimental

Equipment Used: Zymark MultiDose with USP Apparatus II

Manual Dissolution Apparatus: USP Apparatus II (1)

Automated Dissolution Apparatus: USP Apparatus II equipped with Zymark MultiDose Automated Dissolution Workstation with MultiFill off-line collection device.

Review of Immediate Release Tablet Formulation Data

Manual Dissolution:

Because of the proprietary nature of the products involved the authors apologize for the unattributed data. However, the data is taken directly from stability summary charts of development formulations.

Table I illustrates an example of a manual dissolution profile out to 26 weeks at 25C/60%RH. The data appears to be consistent and no trend is observed.

Table I : Formulation-1

Storage Time	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III
Initial	Not Tested	Not Tested	98
12 Weeks	84	98	99
26 Weeks	84	97	99

Table II extends the data to 52 weeks. An increase in dissolution is noticed. A trend to a faster dissolution is unexpected.

Table II: Formulation-1

Storage Time	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III
Initial	Not Tested	Not Tested	98
12 weeks	84	98	99
26 Weeks	84	97	99
52 Weeks	96	101	100

Table III illustrates a second formulation in the same series as Tables I and II. A trend towards slower dissolution is apparent. The concern now becomes: in terms of formulation selection, at 26 weeks should formulation-1 stay on stability and should formulation- 2 be terminated?

Table III: Formulation-2

Storage Time	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III
Initial	Not Tested	Not Tested	99
12 Weeks	98	101	100
26 Weeks	77	97	101

At 52 weeks, formulation-2 as shown in Table IV has acceptable dissolution. Both of these formulas exhibit time point specific variability that may be attributed to the different analysts who performed the tests at each time point.

Table IV: Formulation-2

Storage Time	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III
Initial	Not Tested	Not Tested	99
12 Weeks	98	101	100
26 Weeks	77	97	101
52 Weeks	92	104	105

Automated Dissolution:

Automated dissolution stability data shown in Table V almost looks contrived. A slowing down at 30C/60%RH condition of this development formula can be observed at the 9 month time point. This slowing down is not observed at 25C/60%RH until 18 months has elapsed. The 30C/60%RH nine month time point is predictive of the 18 month 25C/60%RH time point. This observation is also shown at the 12 month time point for 30C/60%RH where the data is mirrored at the 24 month time point of 25C/60%RH. Therefore, one can conclude that the 18 month time point at 30C/60%RH will be predictive of the 36 month time point for 25C/60%RH and a decision can be made 18 months before real time data is available.

Table V: Formulation-3

Condition/ Months	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III	Disso.Time Point IV
Initial	98	100	100	100
25C/60%RH
3	98	99	99	99
6	97	99	99	100
9	---	---	Not Tested	---
12	94	98	98	Not Tested
18	53	97	98	98
24	40	81	98	8
30C/60%RH
3	99	99	99	100
6	95	9	99	99
9	58	96	96
12	39	83	97	Not Tested
18	18	45	66	82

Table VI is the second in the same series of formulations. Once again decisions based on 30C/60%RH data will reduce the amount of testing and time required for formulation selection.

Table VI: Formulation-4

Condition/Months	Disso.Time Point I	Disso.Time Point II	Disso.Time Point III	Disso.Time Point IV
Initial	100	102	102	102
25C/60%RH
3	98	100	100	100
6	96	98	98	98
9	---	---	Not Tested	---
12	94	98	98
18	47	93	97	97
24	33	88	98	98
30C/60%RH
3	99	100	100	100
6	92	97	97	97
9	57	95	96	96
12	34	88	98	Not Tested
18	10	36	62	84

Automated dissolution data is high quality and predictable with low variability. ICH(2) guidelines for accelerated data at 12 months 30C/60%RH are validated for formulation 3 and 4.

The true power of highly reproducible analytically accurate automation can now become a routine tool for management decision making.

Conclusion

In conclusion, automated methods are generally accepted as a resource management tool, and decisions on the purchase of automated equipment have historically been made on the productivity/amortization versus manually executed costs(3). Evaluation of the automated data presented above indicates that decision making and time to market for development formulations adds a new dimension to the "go/no go" implementation of automated systems in development groups.

*To whom to send all correspondence.

References