Hello, I'm
Andrew Basalla
Pharmaceutical and
Machine Learning Scientist.
Hello, I'm
Pharmaceutical and
Machine Learning Scientist.
Learn about my
I am currently pursuing my PhD at the Unviersity of Texas at Austin School of Pharmacy in the devision of Molecular Pharmaceutics and Drug Delivery. I am studying under Dr. Bill Williams and Dr. Zhengrong Cui where my goal is to improve drug delivery of pharmaceutics by improving thin film lyophilization techniques using my background in formulation development, analytical techniques, and machine learning. I earned my Master of Science degree in Pharmaceutical Science from the University of Colorado Anschutz School of Pharmacy. While I was there I did a research thesis titled "A Novel Approach for the Correction of Absorbance Measurements for Light Scattering". I partnered with KBI Biopharma and First Principles Biopharma for this project where I also published this work in the Journal of Pharmaceutical Sciences where that publication is open source and can be read online. Through the coursework, I took classes relating to mass spectrometry, machine learning, drug delivery, and protein formulation, just to name a few. Before this, I earned my Bachelor of Science degree in Chemical and Biological Engineering with a minor in Biomedical Engineering from the University of Colorado Boulder School of Engineering. While I was there I worked in a reasearch lab under Dr. Gin and Dr. Noble where I worked to create new lyotropic liquid crystalline membranes for desalnation of water and iron flow battery purposes. A couple of those projects that I worked on were also published, see my publications section below. Through this coursework, I took courses related to biomaterials, drug kinetics, drug discovery, and computational engineering.
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Before starting my PhD, I was a researcher and lab manager at the Proteomics Mass Spectrometry Facility at the University of Austin Texas. In this role, I analyzed samples for researchers using high resolution mass spectrometers, and gained expertise of this analytical technique. I effectively implemented DIA analysis into the core facility along with the data analysis pipeline. I also learned how to run, analyze, and decided which fragmentation techniques (ETD vs HCD vs EtHCD) would allow for PTM localization compared to sequence identification, etc. I also helped to implement a de novo sequencing data analysis pipeline for the core which is used by the top antibody scientists at UT Austin. Additionally, I utilized my coding and data science skills to develop and employ new technology to automate routine system suitability testing and data management to free up lab researcher's time. Furthermore, I worked closely with bioinformatics researchers and I have implemented, fine-tuned, and utilized some of the latest machine learning models in bioinformatics for mass spectrometry. I have also given lectures about the basics of mass spectrometry to graduate students and other researchers. Before that, I worked at KBI Biopharma in Louisville, Colorado as a lead formulation scientist. At KBI, I started on the biophysical sciences team where I learned and became fluent in all biophysical methods including AUC, CD, DSC, FTIR, fluorescence, DLS, and DSF. After being on the biophysical team, I tranisitioned to the biochemical team where I learned and became fluent using HPLC, UPLCs, their associated methods, and was KBI's subject matter expert in light scattering (MALS and DLS). Additionally, I became fluent in mass spectrometry having used Q-TOFs, TOFs, Orbitraps, and LTQs and was the mass spec lead on multiple projects. Through this work, I was leading formulation development projects, where I would design and execute iterative statistical based (DOE) development projects for many pharmaceutical modalities. In addition to my wet-lab scientist role, I also lead data science efforts at at KBI. Using my fluency in Python and Dash, I developed multiple python applications which could reduce analysis time for scientists or fix problems. Notably I designed a tool which could correct absorbance measurements for light scattering which was published in the Journal of Pharmaceutical Sciences in 2023.
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My programming language of choice is Python and overall I am very fluent in it. I started coding back in my undergraduate coursework and started using Python during my time at KBI and in my Masters thesis work. During this work, I quickly learned the basics of using Jupyter notebooks, importing data, using pandas for dataframe management, and plotly for data visualization. From working with First Principles Biopharma, one of the companies hosting my thesis work, I learned Git and Github for version control, collaborations, and working on a programming team. During that experience, I also learned how to use Plotly's Dash and Docker for generating and deploying web based applications using Python and I implemented my thesis work on their website. More recently, I use python and pytorch for machine learning applications. At the proteomics core, I have implemented, fine-tuned, and utilized some of the latest machine learning models in bioinformatics for mass spectrometry. For example, I have used AlphaPeptDeep for retention time and MS2 fragmentation prediction, DeepNovo for de novo peptide sequencing, and protein language models like progen2 for peptide to protein assembly. Additionally, I have trained convolutional neural networks for image prediction and random forest regression tree models both for formulation development which, during my Master's work, I also had given a lecture how to implement. At KBI, I used my Python skills to develop multiple applications which could remove critical bottle necks in analytical workflows. One application I made would decipher and deconvolute large proteomic mass spectrometry datasets to remove the time that scientists would spend exporting data by hand. Additionally, I created tools for determining nucleic acid content in viral capids and of course the tool for correcting absorbance spectra for light scattering. Past that, I have experience using other programming languages including, HTML, JavaScript, and CSS (which this website is made from), VBA, and matlab. I also have experience using bash scripting and Linux operating systems.
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Here are the publications that I have been fortunate to work on:
Basalla, A.J., Kendrick, B.S. 2023, Correcting Ultraviolet-Visible Spectra for Baseline Artifacts. Journal of Pharmaceutical Sciences, Volume 112, Issue 12, 3240 - 3247.
McGrath, M. J., Hardy, S. H., Basalla, A. J., Dwulet, G. E., Manubay, B. C., Malecha, J. J., Shi, Z., Funke, H. H., Gin, D. L., & Noble, R. D. 2019 Polymerization of Counteranions in the Cationic Nanopores of a Cross-linked Lyotropic Liquid Crystal Network to Modify Ion Transport Properties. ACS Materials Letters, 1(4), 452–458.
Dwulet, G. E., Dischinger, S. M., McGrath, M. J., Basalla, A. J., Malecha, J. J., Noble, R. D., & Gin, D. L. 2019. Breathable, Polydopamine-Coated Nanoporous Membranes That Selectively Reject Nerve and Blister Agent Simulant Vapors. Industrial & Engineering Chemistry Research, 58(47), 21890–21893.
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