Development of Universal, Automated Sample Acquisition

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Development of Universal, Automated Sample Acquisition, Preparation and Delivery Devices and Methods for Pharmaceutical Applications Gordon Randall Lambertus, Luke P Webster, Timothy M. Braden, Bradley M. Campbell, Jennifer McClary Groh, Todd D. Maloney, Paul Milenbaugh, Richard D Spencer, Wei-ming Sun, and Martin D. Johnson Org. Process Res. Dev., Just Accepted Manuscript • DOI: 10.1021/acs.oprd.8b00280 • Publication Date (Web): 12 Dec 2018 Downloaded from http://pubs.acs.org on December 13, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

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Organic Process Research & Development

Development of Universal, Automated Sample Acquisition, Preparation and Delivery Devices and Methods for Pharmaceutical Applications Gordon R. Lambertus,†* Luke P. Webster,† Timothy M. Braden,† Bradley M. Campbell,† Jennifer McClary Groh,† Todd D. Maloney,† Paul Milenbaugh,††† Richard D. Spencer,†† Wei-ming Sun,† Martin D. Johnson† †

Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46285, USA

††

Eli Lilly SA, Dunderrow, Kinsale, Cork, Ireland

†††

D&M Continuous Solutions, LLC, Greenwood, IN 46113, USA

ACS Paragon Plus Environment

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Automated Sample Preparation and Delivery Acquire Sample

Report Results

Prepare Sample

Automate Process Data

Deliver Sample

Online Chromatography


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ABSTRACT

Continued emphasis in the pharmaceutical industry towards development of hybrid and continuous processes has led to a resurgence in process analytical technologies. The need to consistently and rapidly monitor the quality of a material being made from these processes is a significant challenge that requires integrated, online analytics. Often the most challenging aspect of implementing realtime monitoring is ensuring that the analytical instrumentation is receiving a representative sample from the process. The Small Molecule Design and Development (SMDD) organization at Eli Lilly and Company has developed a highly adaptable process-to-analytics interface that has been broadly implemented across the development portfolio. The automated sample carts use only gravity and low pressure nitrogen to obtain representative process samples, typically on the order of 0.3 – 6 mL. Subsequent sample preparation operations including quenching, derivatization, and most commonly dilution (10-250x is customary, but not restrictive) in an HPLC compatible diluent. Samples are then delivered to the receiving online chromatographic instrument in a manner conducive to injection and analysis for that specific platform.

These carts have

demonstrated robust performance and qualification data routinely meets 1/2 inch o.d. for aqueous streams), that for heterogeneous liquid\gas matrices (intermittent flow or reactive gases, e.g. hydrogenations), the vapor can bubble up through the tee and out the overflow arm. The overflow (of both liquid and gas) is then directed towards a product tank or another continuous unit operation. The overflow Tee can be as little as 3/8” compression fittings with 1/16” inlet and outlet tubing for research scale or 3/4" compression fittings with 3/8” inlet and outlet tubing for production scale. It is important to note that at low reactor throughputs (e.g. 0.02 mL/min), automated sampling carts using this configuration will consume a significant fraction of the process material.


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From Process

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Process Return

A From Diluent Measure Out

B Diluent Wash Zone

To Mixing Fluidics

Figure 3: Schematic showing the process sampling interface of the automated sampling cart. A (generally open) and B (generally closed) valves together form the sampling zone on the automated sample cart and the volume of the gap between the balls of the valves define the sample volume. Bold arrows indicate direction of process flow.

The “from process” line is the input to the overflow Tee and comes from the upstream unit operations (PFR, CSTR, etc.). The outlet of this tube is located such that process material exits the tube just above A valve, shown in Figure 3. This proximity close to the A valve allows for complete flushing of the overflow Tee and the sample volume as the process material enters the overflow Tee. As the Tee operates normally liquid filled, all excess material exits via the side leg labeled “to product collection”. However, at low flow rates the interior of the ball of A valve can act as a low dead leg, which is overcome by taking waste cuts. A valve isolates the sample to be prepared by the cart from the rest of the process. It is normally open to ensure that material in the sample zone is representative of that specific process time is isolated for preparation. The inlet dip tube extends as close to the ball of valve A as possible. B valve isolates the sample volume from the rest of the fluidics on the automated sample cart and is normally closed. When both valves


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are closed, one of the steps in sample acquisition, the fixed volume between the two valves is isolated. This is the neat process sample to be used by the cart. The simple, highly flexible, and adaptive design of the process interface for the automated sampling carts has made them the most widely deployed piece of equipment in our development laboratories. While maintaining containment within the processing equipment, this interface offers minimal risk to the process as there are no automated valves or sample loops in the main process flow path and the only direct process contact with the sampling cart are the overflow Tee and A and B valves. Valve interlocks are programmed into the automation, preventing a situation where both A valve and B valve can open at the same time. By doing this, dilution solvent cannot get into the process stream. Any failure (mechanical, automation) on the sampling cart that causes it to shutdown, will not impact the process in anyway, as both valves are fail closed.

2.3 SUMMARY OF CART OPERATION The design of the automated sampling carts provides maximum flexibility in dilution factor by using modular, interchangeable sample and dilution zones. The lower end of the dilution range is more operationally challenging with this cart as the volume in the downstream sample delivery fluidics makes it more difficult to move smaller diluted sample volumes. The cart is simple in design, easy to integrate, and operates at room temperature utilizing only house nitrogen (15-45 psi) and automated valving (based on either timing or pressure control) to move material from one zone to another. The sampling and mixing components of the sequence typically take 1-3 minutes to execute, while the sample delivery process can take an additional 2-15 minutes to complete. Sample delivery time is governed by the physical location of the analytical instrument relative to the dilution cart (distance between the sample cart and the analytical instrument), the length and


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internal diameter of the tubing, viscosity and volume of the diluted sample, and the nitrogen pressure available. Designed to be small and mobile, the sampling cart is ideal for colocation with the reactor. Having the sampling device proximal to the reactor helps to maintain sample integrity by collecting it and preparing it within a minimal amount of time. Additionally, the sampling carts have been built using all electrically classified components and can reside on a manufacturing plant floor. With the ability to push samples long distances using nitrogen, analytical equipment does not need to be collocated with the process. As a result, analytical equipment can reside in nearby non-classified laboratories, saving both capital investment and operational complications.

3. DISCUSSION The universality and simplicity of the process interface for the automated sampling carts has made them applicable across a wide range of applications that relate to pharmaceutical development and manufacturing. This discussion will first address general performance characteristics of dilution carts and assessment on case-to-case basis. The utility of the carts across diverse applications will be illustrated through three sections, 1) a cradle to grave application on a continuous reductive amination reaction where carts were implemented from small scale development runs through large scale manufacturing, 2) highlight a variety of unique sampling challenges experienced across applications in development laboratories, and 3) illustrate qualification strategy, operational performance, and application in GMP manufacturing. Modifications to the functionality and operation of the cart will be highlighted relative to each section.


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3.1 PERFORMANCE ASSESSMENT Performance assessment of automated sample carts typically relies on the downstream analytical measurements. Critical metrics monitored include precision, carryover, dilution factor, and assessment of fouling risk.

Most routinely, online HPLC is used to assess performance

characteristics of the dilution carts. Precision is determined by calculating the relative standard deviation of a set of samples at a steady state condition. During performance qualification this is often done by recirculating a representative process sample through the process sampling interface, and preparing and analyzing a series of diluted samples of the same material in a mock steadystate scenario. An RSD of the peak area via HPLC (or GC) can then be calculated and used to understand analytical variability within the automated sample cart/HPLC combination. In cases where potency of the sample is a consideration, the accuracy of the dilution is important to understand as well. The dilution factor for a specific cart is set by the ratio of the diluent volume (dilution zone in Figure 1) to the sample volume (volume between A and B valves in Figure 3). The theoretical dilution factor provides a close approximation of the true dilution. A more accurate method of determining volumes would rely on capturing several aliquots (10-20) dispensed by either the sample zone or the diluent zone and averaging the weight (and thus volume corrected by density) of the collected material. These volumes can then be used in determination of the concentration of diluted samples, and thus the dilution factor achieved by the cart. Alternatively, this value can be approximated by comparison against a calibration curve where samples are analyzed via the same mode on the analytical instrument. To do this, calibration standards should be run in an online mode, similarly to process samples, in order to generate reliable quantification of online samples.


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Over time, the automated sampling carts have routinely performed with very good precision. Relative standard deviations of 99% of the out of specification material. The model was confirmed using data from the second automated sampling cart and online HPLC (on the deprotection reaction) that was used to monitor this impurity in downstream unit operations. Effected material was then diverted from the process and quarantined. The same RTD model was used to calculate the time required to remove all affected material from the system. This material was also diverted and quarantined. Within 4 hours of restarting (~165 hours) the impurity returned to an acceptable level and material was redirected back to normal collection. Robust and reliable performance and thorough qualification packages have led to frequent manufacturing installation of these sampling systems. Specific examples here highlight sampling cart installations within Eli Lilly and Company small molecule development and manufacturing sites.

The value of these installations for building process understanding through process

monitoring for continuous manufacturing is presented. Although these examples focus on installations in Eli Lilly and Company manufacturing sites, the carts have been used at several contract manufacturing partners on a variety of applications not covered here.

5. CONCLUSIONS One of the primary challenges in developing and implementing continuous processes is the increased analytical burden associated with process monitoring. Operators and QC laboratory


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resources would rapidly be overwhelmed with the frequency of sampling and analysis required to support these functions. This work addresses that primary bottleneck and significantly reduces the number of penitential sources of error by automating and integrating these operations with the process. Integration to online analytical tools further allows for more efficient generation of time critical data that can be converted to process relevant information on a meaningful timescale to enable continuous manufacturing in pharmaceuticals. Online HPLC is one of the preferred platforms for supporting continuous processes, and to fully realize its benefits requires robust and representative process sampling tools with a universal interface allowing integration to reactors of all types and scale. The sampling carts described here have been deployed across the small molecule portfolio at Eli Lilly, including a wide range of reactor platforms, reaction conditions, and process scales. The functional description of the carts detailed the universal interface for representative process sampling in addition to the required sample preparation operations. Fluidic design of the sample-to-instrument interface allows for integration to a variety of online HPLC and GC equipment, including the use of existing bench-top equipment. Within the development laboratories, these carts have prepared tens of thousands of process samples for analysis. This investment translates from development to manufacturing as the tools are designed to use exact replicas in manufacturing. Qualification packages were disclosed along with several case studies highlight implementation in manufacturing. Substantial efforts are ongoing to continue to improve the performance of these sampling carts as well as to expand the scope of application.


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5.1 ASSOCIATED CONTENT Supporting Information. Operational descriptions of the automated sampling carts along with fluidic diagrams are included in the supporting information.

5.2 AUTHOR INFORMATION Corresponding Authors *E-mail: Gordon Lambertus: [email protected] Notes The authors declare no competing financial interest.

5.3 ACKNOWLEDGMENTS We would like to acknowledge the following individuals from Lilly Research Laboratories (Indianapolis, IN, USA): Michael Miller for contributions to online HPLC and Joel Calvin, Edward Conder, Richard Cope, Brian Haeberle, Phillip Hoffman, Ryan Linder, Scott May, Nikolay Zaborenko for helpful discussions related to process integration and understanding. We would like to acknowledge the following individuals from Lilly Manufacturing (Kinsale, Ireland): Ashley Humenik and John Howard for engineering contributions and Kenneth Desmond, Paul Desmond, and Noel Sheehan for qualification and implementation contributions. We would like to acknowledge the following individuals from D & M Continuous Solutions (Greenwood, IN, USA): Ed DeWeese, Richard Spears, Edward Chow and James Stout for contributions to construction and implementation. We would also like acknowledge Timothy Weaver from


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Development of Universal, Automated Sample Acquisition

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