Description

The delivery of injected drug therapies is a broad, multidisciplinary process, encompassing needle insertion, injection, and target site delivery. A comprehensive understanding of each step is vital for optimal drug administration. This student team will focus on cutting-edge pharmaceutical research, aiming to enhance our understanding of the injection process to advance global healthcare and benefit patients worldwide. The team will have access to advanced research technologies and will develop tools and protocols to address critical research inquiries.

Student teams will be formed based on interests and expertise to work on the following projects.

Pharma with the LPRC – T1: Microfluidic system for studying the transport of therapeutics.

Faculty Advisor: Prof. Arezoo M. Ardekani

The development of a microfluidic model for various therapeutics, ranging from various sizes and concentrations, will be explored. Transport within the hydrogels will be analyzed to generate correlations with the various aspects of the therapeutic solutions.

Project description: Microfluidic models have been recognized as an interesting alternative to animal models for drug screening. These models can mimic some of the physiological characteristics across solid tumors to the physiological barriers. The therapeutic solution will be injected into one of the microchannels, while the other microchannel wells will have the hydrogel formulations in them. The transport of the therapeutic solution in the hydrogel will be measured by fluorescence microscopy or other techniques. 

Prerequisites: Biomaterial synthesis and fluorescence microscopy techniques are a plus, but not a requirement.

Pharma with the LPRC – T2: Improved protocols for characterizing scanning probe microscopy tips for use in pharma fabrication processes.

Faculty Advisor: Prof. Ryan Wagner

Project Description: Three broad classes of microscopes use different physical mechanisms to magnify small objects.   Optical microscopes use light focused by lenses.  These are reliable but are mostly limited to resolutions greater than 300 nm.  Electron microscopes use a beam of focused electrons.   These can achieve atomic resolution but are mostly limited to electrically conductive samples and operating in vacuum environments.  Scanning probe microscopes (SPM) use the interaction of a sharp tip with a surface.  These can achieve atomic resolution in air and liquid environments on conductive and non-conductive samples.

Because of SPM’s strengths, it is broadly used to characterize soft biological matter; however, these measurements suffer from issues of reliability.  The result of an SPM measurement strongly depends on the shape and chemical composition of the sharp tip.    It is difficult to control the exact tip shape during manufacturing.  Additionally, while collecting data mechanical forces can change the tip shape through wear and fracture and adhesive forces can change the tip chemistry as parts of the sample can break off and stick to the tip.

In this project, the team will try to improve the reliability of SPM measurements by developing, testing, and documenting improved methods of characterizing the condition of SPM tips.  This could involve measuring the tip with electron microscopy, making SPM reference measurements on different samples, and developing protocols for modifying tips.   If the first part of the project is successful, the team will characterize SPM tips for use by the broader Eli Lilly-Purdue project.

Pharma with the LPRC – T3: Interdisciplinary approach to overcome cellular tomography challenges.

Faculty: Prof. Lauren Ann Metskas

Project Description: Cellular tomography has unique challenges compared to other tomography pipelines. These challenges often require computational methods to overcome. Two specific challenges we foresee are 1) the inability to seed a sample with fiducial markers, requiring cellular landmarks to align tomograms and 2) identifying and picking the particles of interest in a 3D volume. There are several programs that can be used to accomplish these tasks, but none work well for all samples. We have found an interdisciplinary approach works best to develop and test new protocols designed for each cellular component of interest. We would look to build a team with undergraduate students from computer science, physics, chemistry, and biology.

Left is an example adapted from (Lui V, Rigort A, Baumeister W. Cryo-electron tomography: the challenge of doing structural biology in situ. J Cell Biol. 2013 Aug 5;202(3):407-19. doi: 10.1083/jcb.201304193. PMID: 23918936; PMCID: PMC3734081) visualizing cryoET orthoslices of intact cells (a-c) and resulting isosurface representations (d-f). Generating the orthoslices requires the alignment of the tomograms collected, while the generation of the isosurfaces requires the ability to identify cellular components accurately. Generating these data for the cells and conditions of interest would benefit from the VIP program and would provide significant experience for the undergraduate students who would participate.

Prerequisites:

• Computer sciences students with familiarity working with linux, bash, matlab, and graphical visualization.
• Physics students to focus on functions and equations to calculate surface area, determining volumes within vesicles.
• Chemistry students and biology students who could explain results and findings in the context of the cellular environment or using structural biology to make observations.

Pharma with the LPRC – T4: Modular auto-injector platform to design testing.

Faculty: Prof. Pavlos Vlachos

A student team will develop a testing platform to evaluate different modular auto-injectors (AIs) designed for a range of therapeutic solutions with varying properties. This testing will analyze how different design factors impact drug delivery.

The market for AI therapeutic devices is growing rapidly, driven by the need for self-administered therapeutics. Design requirements for AI devices vary due to factors like fluid properties, patient comfort, safety, and cost. A computational model has been created to estimate these requirements, but they need validation through rapid, high-throughput testing. The team will assemble modular AI devices through rapid fabrication and test them for device movement (kinematics) and injection rate into a substrate. Data from sensors like accelerometers and high-speed cameras will be collected and analyzed.

Pharma with the LPRC – T5: Subvisible particle characterization of therapeutics.

Faculty: Prof. Pavlos Vlachos

A student team will use a new imaging platform to develop tools for identifying subvisible particles (SVPs) in various therapeutics. These tools will help assess what fraction of the therapeutic remains undelivered after drug administration.

The FDA regulates auto-injector therapeutics and considers the presence of insoluble drug particles – SVPs – during drug delivery. These SVPs can lead to injection site irritation and immunogenic responses. Identifying insoluble products is challenging due to variations in SVP shape and size. The team will explore innovative methods for collecting SVP characteristics through imaging and develop platforms to identify SVPs based on these characteristics.

Prerequisites: Basic proficiency with Matlab and/or Python strongly desired.