Tyler Josephson’s lab sits off a main corridor in the department of chemical, biochemical and environmental engineering at UMBC. Open the door, though, and you’ll see nary a beaker, chemical closet, or lab coat. Inside, a few computers sit on tables. You might see equations scrawled on the white board or a few students poring over lines of code.

Using this modest setup, Josephson has launched an ambitious project to equip computers to make scientific discoveries—starting in the realm of chemistry. This March he won a prestigious NSF CAREER award to advance the project.

The goal of the work is ultimately to speed up the process of science, which should in turn give humanity new knowledge and tools to face down big challenges such as climate change and environmental degradation.

As Josephson and his students dive into the work, they are bringing together techniques from across mathematics, computer science, and chemical engineering. Their first step is to translate chemical theories into a rigorous mathematical language that a computer can understand.

Math as the language of science

In 1623, the Italian natural philosopher Galileo Galilei wrote an essay in which he described nature as a book written in “the language of mathematics.” Many scientists since have puzzled over the mysterious power of math to describe physical phenomena.

Josephson and his students are tapping into this power. They are using a tool developed by researchers at Microsoft called the Lean theorem prover. Lean is both a computer language and a program for checking each step of a rigorous mathematical proof.

“Formal proofs, which are verified by a computer, differ from the informal, handwritten versions often used by scientists,” says Josephson. Informal proofs are easier to write, but they usually skip logical steps, assuming a human reader will have the knowledge and skill to follow along. This means that errors can creep in undetected.

On the other hand, if a proof has been written and checked in Lean, it is guaranteed to be correct as long as the stated assumptions are true.

A community of Lean programmers

Lean has a dedicated community of volunteer developers who have built a large library of mathematical proofs, each of which can then serve as a building block for more complicated proofs. They aim to digitize mathematics, starting with the entirety of the undergraduate math curriculum, which will lay the foundation for formal proofs in advanced modern mathematics.

Josephson plans to build a similar library with formally correct derivations in science and engineering, starting with chemical concepts such as the thermodynamic behavior of gases and of molecules sticking and unsticking from surfaces.

He and his students describe their approach in a first paper on the subject, and are in the process of submitting it to journals.

The power of the work will multiply as more of the foundations of science are translated into Lean, so a large part of the team’s work will also be to recruit, inspire, and train fellow proof creators. They will hold workshops to showcase Lean for scientists and engineers, and they plan to create fun and educational games that will teach Lean-programming skills to newcomers.

“I’m really excited to share this tool with students and the scientific community,” Josephson says.

Building better scientific computing tools

Josephson’s goal to formally verify scientific theories isn’t just an intellectual exercise—it’s a means of building better tools for better science. One such tool he plans to create with NSF CAREER award support is Lean-based computer software that can simulate the behavior of molecules under a range of conditions. 

Scientists often use such software to test theories as an alternative to physical experiments. It can be easier to run simulations of reactions on a computer, for example, than to mix real chemicals again and again, and some molecular phenomena may happen so fast, or under such extreme conditions, that current experimental tools cannot capture them.

However, bugs can mar the performance of the software. For example, starting in 2011, a hidden coding error fueled a seven-year “war over supercooled water,” in which two scientific groups disagreed about what happens to ultrapure water when it is cooled significantly below the freezing point of normal water, and then suddenly crystallizes.

Code written in Lean is unique from that written in the programming languages commonly used in scientific computing, since it can be provably free of such math errors, Josephson says. 

As more scientists and engineers learn to write code and proofs in Lean, others will be able to write bug-free software for applications as diverse as weather forecasting, drug discovery, and predicting material performance.

“AI scientists” who reason on their own

Ultimately, Josephson hopes to use a Lean-based library of scientific knowledge to train computers as fellow scientists. For example, large language models, such as the recently popularized ChatGPT, might be trained on a library of scientific proofs and gain the ability to “autocomplete” proofs on their own, translate informal proofs from the literature into formal ones, and even discover entirely new scientific theories, which could then be checked for correctness by Lean.

A tool like this might revolutionize science. In Galileo’s time, a single person could master large portions of human scientific knowledge, but now scientists usually go to school for decades to become experts in a tiny subfield, Josephson says.

AI scientists capable of digesting a database of thousands of scientific proofs in multiple disciplines might draw connections across them to reveal new discoveries. “Such a tool could lead to an AI-powered Renaissance in interdisciplinary scientific discovery,” says Josephson.

While such lofty goals remain in the future, Josephson and his students are energized by the possibilities. As they embark on an exciting scientific journey, they are thrilled to bring as many people as possible along on the ride.

Positionally statement: This post is written by Audrey Gatewood. I am a senior in the UMBC School of Social Work, completing my field placement at the Women’s Center. I’m writing this blog as a result of learning about reproductive technologies in my personal life, with the belief that other people may be interested too. I do not have any background in medical education, and do not have first- hand experience with reproductive technologies. This blog is written from research I’ve done for myself, prompted by my own interest in using reproductive technologies, and does not cover everyone’s experience or all possible circumstances in which reproductive technologies may be used. 

(A simplified illustration of the difference between artificial insemination, in which sperm is injected directly into the uterus, and in vitro fertilization, in which an egg is fertilized in a petri dish before being inserted into the uterus. Photo via https://www.invitra.com/ ) 

When I mention my partner and I may consider having kids, generally a beat of intrigued confusion follows. My partner and I are both women, and cannot get pregnant on our own. Even surrounded by other LGBTQ people, follow up ensues: Adoption? Intrauterine insemination? Sperm donor? 

Fertility is typically viewed as a given for people of a certain age, and parenthood as inherent in long-term heterosexual partnerships. For women in particular, fertility and motherhood are seen as defining states of being. But what about people who are infertile, who can’t get pregnant for health reasons, who want children but don’t want to be pregnant, who are older, lesbian and gay couples, and so on? Disrupting the typical image of childbearing comes with many questions of intention, method, and outcome. Particularly interesting are the medical technologies and methods that people may use to get pregnant, called artificial reproductive technology, or ART. 

Artificial reproductive technologies are innovations in healthcare that help people conceive. According to the American Center for Disease Control definition, ART includes 

“any fertility-related treatments in which eggs or embryos are manipulated. Procedures where only sperm are manipulated, such as intrauterine inseminations, are not considered under this definition (Jain and Singh, 2023).”

The most well known and common ART procedure is in vitro fertilization, or IVF, in which a sperm and an egg are combined outside of the body in a laboratory dish. Eggs are retrieved in a process called ovarian stimulation, in which a person is given hormonal fertility medications to stimulate multiple egg growth in the ovaries, instead of just one per month (Jain and Singh, 2023). This way there are more chances for the egg to be effectively fertilized and result in a pregnancy, as not every egg will fertilize, and not every fertilized egg will result in a full term pregnancy. The fertilized egg, or multiple eggs, are then transplanted into the uterus, where they may or may not attach to the uterine lining and develop into a pregnancy. 

(Illustration of the in vitro fertilization process. Photo via dreamstime.com)

In this same process, one could choose to have eggs and/or embryos frozen for future use in a process called cryopreservation (Jain and Singh, 2023). This saves the person from having to go through the process of ovarian stimulation again, as it’s a relatively involved, 1-2 week long process that requires many doctors visits and potential side effects from hormone fluctuation. Some people choose to use cryopreservation to preserve eggs before undergoing major health undertakings, like chemotherapy, to prevent eggs from being damaged, or if age is a concern, one may choose to freeze their eggs at a younger age and use them at a later time, when they are ready to be pregnant.

IVF is the most common ART in use, but there is also intrauterine insemination, or IUI. IUI is the process of inserting sperm directly into the uterus around the time of ovulation to increase the chance of fertilization (Planned Parenthood). Sperm is collected either from a partner or from a donor, “washed” in a process that collects healthy sperm and removes chemicals in the semen, and inserted via a catheter. The process is much more low- tech than IVF, less invasive, and generally takes about 5-10 minutes. But how do you get pregnant when sperm isn’t readily available? Most likely through a sperm bank, using donor sperm. 

(Illustration of the intrauterine insemination process, in which washed sperm is injected into the uterus via a catheter. Photo via Jonathan Dimes for BabyCenter)

People may choose to use donor sperm for a variety of reasons: if their/their partner’s sperm is infertile, to avoid passing down hereditary diseases, if a single woman is ready to have a kid, or if neither partner can produce sperm, like many lesbian couples, for example. People can use sperm from a friend or relative, but often sperm is coming from donors with varying levels of anonymity. Whether and to what degree a donor remains anonymous depends on the sperm bank and policies local to the state and country. Generally, though, total anonymity cannot be guaranteed to a sperm donor, particularly with the rise of consumer-level DNA testing for websites like 23AndMe or Ancestery.com. Generally, a medical history and varying levels of descriptors are provided to a person or couple looking to use donated sperm, descriptors that may include hair color, self-reported personality traits, ethnicity, personal interests/hobbies/ career, and sometimes, though not always, a photo. Sperm donors are heavily screened for infectious and hereditary disease, undergoing extensive medical questionnaires, full physical exams, and sperm analysis. Donors will also go through mental health screening and a criminal background check (UCSF Health 2020). 

ART and other related procedures like IUI come with a price. A single IVF cycle can range from $15,000 to $30,000 on average (Forbes Magazine, 2023). IUI can cost between $300 to $1,000 per session, depending on if donor sperm is used (Planned Parenthood). Neither procedure guarantees a full term pregnancy. In fact, national data from the Society for Assisted Reproductive Technology reports that “the rate of live births following first-use IVF for women under the age of 35 using their own oocytes is only 37% (Center for Reproductive Rights, 2020)”. Private insurance companies may cover some or much of the procedure, and there are grants, discount programs and clinical studies that can reduce the cost  (Forbes Magazine, 2023). 

Even so, fertility treatments come with a barrier of accessibility, and may only be available to those who can afford them. IVF in particular can be burdensome for those who utilize it, not only coming at a huge financial cost, but demanding an investment of time and emotional and physical strain, causing many people to discontinue using it after an unsuccessful first attempt. 

IUI faces a much lower barrier of accessibility, but is not an option for everyone in need of fertility assistance. In addition to being financially inaccessible for many, infertility or using ART can come with a stigma, one which typically affects women. Deviance from the typical fertility narrative challenges the societal expectation of women as inherently mothers, and of the normative family dynamic of a married man and woman having children ‘naturally.’ Women using ART due to fertility issues may experience social stigma, personal shame, and anxiety or depression (Center for Reproductive Rights, 2020). Despite the fact that male-factor infertility accounts for 50% of clinical cases, women tend to receive the brunt of this stigma. For lesbian couples using IUI, stigma can follow the couple through their whole lives as a family, as the rules of a normative family structure are broken when a man is removed from the equation, and when pregnancy is achieved in a non-normative way. 

 There isn’t much representation of lesbian moms. Even surrounded by my sizable LGBTQ community, in a “progressive” city, I haven’t had many examples of what parenting as a lesbain couple could look like. Sometimes I find myself wondering, if I had a kid, what their experience would be like having two moms? Will it be a huge difference from how I grew up? How would our family be treated by others? Will they be asked invasive questions about their birth? How much would they look like the sperm donor? What if they got in touch with the sperm donor when they were older, and what would that mean?

 Regardless of these questions, I’m grateful that reproductive technologies exist, and hope to see barriers to access removed. The future potential for growth, not only in the technological aspect, but in the regulation and accessibility of consumer use of fertility treatments, and of societal understanding, points to ongoing questions about medical technology, genetics, parenthood and more. 

Reference 

Center for Reproductive Rights. (2020).  Infertility and IVF access in the United States. 

Forbes Magazine. (2023, March 7th). How much does IVF cost?. Forbes. 

Jain, Meaghan; Singh, Manvinder. (January 2023)  Assisted Reproductive Technology (ART) techniques. National Center for Biotechnology Information.

Planned Parenthood. What is intrauterine insemination (IUI)? 

UCSF Health. (2020, October 7). Donor sperm insemination. ucsfhealth.org. 

Joana Hernandez

Degree: B.S., Chemical Engineering, biotechnology & bioengineering track
Hometown: Hyattsville, MD
Post-grad plans: Applying to biochemical engineering Ph.D. programs

McNair Scholar Joana Hernandez is a research enthusiast who found her interest in scientific exploration and mentorship while at UMBC. Since 2019, Hernandez has worked as a research assistant in the lab of Fernando Vonhoff, assistant professor of biological sciences. The lab uses fruit flies as a model to study human neurological diseases. It was in Vonhoff’s lab where she realized that there were opportunities to turn her love of learning into a career in research. 

Hernandez has taken her interest in conducting research to the next level by helping to guide fellow students who may be unfamiliar with the academic research process. As a teaching fellow in the McNair Scholars Program, Hernandez led workshops in a class dedicated to teaching students how to develop research proposals. During these workshops, she presented on topics ranging from how to give a research presentation to how to apply to Research Experiences for Undergraduates (REUs). 

Hernadez shares that she’s proud to be a McNair Scholar. “As a first-generation college student, it can be difficult to navigate academic spaces and obtain resources on applying to graduate programs,” Hernandez says. “McNair welcomed me with open arms and helped grow my confidence by providing me with opportunities to conduct research and present at national conferences.”

Has there been a mentor or fellow student who influenced your time at UMBC?

“My mentors Fernando Vonhoff and María Célleri, assistant professor of gender, women’s, and sexuality studies, have both had a positive influence on me. As a first-generation college student, I was unaware that undergraduates could participate in research or present at research conferences. When Dr. Vonhoff enabled me to join his lab my freshman year, it opened the doors to a lot of future opportunities. I am very grateful to have had a research mentor that was so understanding and encouraging.

“Dr. Celleri, my McNair mentor, is someone I can always count on to give me advice about navigating academic spaces as a Latina, and how to balance my life between my immigrant household and school. I appreciate all the wisdom I have gathered from her.”

What academic achievement are you most proud of?

“I am most proud of when I presented the research I did in the Vonhoff lab at the 2019 Annual Biomedical Research Conference for Minoritized Scientists (ABRCMS). That was the first time that I had attended a national conference and flew out to the West Coast. It was an eye-opening experience being able to see other undergraduate researchers from diverse backgrounds who were also just as passionate about communicating their work.”