From Democratizing IVF: Using Science, Medicine, And Engineering (And Venture Capital) To Help Build Families
During fourth year of med school, I made the rounds of the academic hospital centers in Boston, New Haven, New York, and Philadelphia. I forget how many interviews I had, but every one of them started with the same question: why ob/gyn? I experimented with different answers. OBGYN is the real primary care. OB/GYN was surgery, plus obstetrics, plus internal medicine. OB/GYN was delivering babies. I loved delivering babies!
In reality, there was a mystique about obstetrics and gynecology that drew me in, but I wasn’t articulate enough to figure out a good way to say that. Midway through my M4 year, I had delivered probably a dozen babies myself, and assisted on a few dozen cesarean sections, each time feeling like a member of an exclusive society. I loved surgery, the discipline of the operating room, the focus that it imposes on everyone around the table. Two, three, four hours: I had no idea where the time went. Surgery made it stand still. I also liked the idea that as an OB/GYN, I could deliver a baby, see her as an adolescent, see her later for birth control, then see her in preparation for motherhood, take care of her during her pregnancy, deliver her baby, and then have her and the baby as patients, a magic cycle. And of course there was in vitro fertilization (IVF).
Nothing I encountered as a premed, or in medical school, seemed as revolutionary as IVF. It was a totally new way to treat patients, combining imaging and medicine combinations and miracle-level laboratory work and procedures — all rolled up to solve a life-stopping problem. But it was more than that: a novel platform that we could use to re-study how pregnancy came about, how it succeeded and how it failed. I had to be part of that.
Which made the Ob/Gyn decision easy, because to get to IVF you had to be an Ob first.
Ob/Gyn training was long, exhausting and immersive, filled with dozens of micro procedures and standard operating practices: bowel preps and venous access for surgery, insulin management for pregnant diabetics, managing emergencies while delivering a baby: bodies that get stuck after the head came out, bleeding that would not stop, placentas that would not let go. The first years were a disorienting catalogue of facts and how-tos, learned, practiced and then taught to the next class of interns. But along with the details and steps by step, greater, more general truths emerged, the most surprising of which was that the science of obstetrics and gynecology was not much of a science at all.
One of the things that drew me to medicine in the first place was the unequivocal good of relieving others’ suffering or curing disease. I left medical school naively assuming that the facts underlying our actions as doctors — the journey from collecting data, analyzing and interpreting and formulating plans — that those facts were equally unequivocal: measurable, reproducible, and evident to all of us, once we had had enough experience.
But as the pace of training slowed from frenzied to just overwhelmingly busy, and as I spent more time collecting data, analyzing and interpreting and formulating, I saw a fuzziness, a lack of discipline to our thinking and acting — even our communicating, down to the names we gave the diseases we treat.
No one used the term “precision medicine” back then. Most of medicine back then was analog, pattern recognition, I know it when I see it analysis. We lionized the bow-tied internists who were blessed with “clinical judgement,” an imprecise term that seemed to be a combination of having a good memory and been around for a long time. As for me, I was too unsophisticated to recognize that medicine in general, and obstetrics and gynecology in particular, was still early in the journey from intuition and magic to data, from analog to digital. Unlike our colleagues in chemistry and bridge building, who used numbers that went far to the right of the decimal point, we still licked the tips of our index fingers and pointed them into the wind.
I filed these observations away, until after I left medicine and studied healthcare as a whole, science and medicine now crossed with business. I started to see how how the disciplines within medicine were stratified. Areas like oncology or inflammatory described their diseases in very specific ways, often at the molecular level. Other fields, like neurology and psychiatry, remained pattern-recognition disciplines giving obscure names like Alzheimer’s disease, or nonspecific descriptions like “pain syndrome” vocabularies that were vague, unmeasurable, and open to anyone and everyone’s different interpretations.
Women’s health, like neurology and psychiatry, is an imprecise discipline. Think of our diagnoses: infertility, dysmenorrhea, premenstrual syndrome, pre-eclampsia, and ovulatory dysfunction. These are very real entities, causing real pain and suffering. They need to be treated and cured, but for now they are still poorly defined, characterized not by abnormal genetic sequences, but by a list of observations or descriptions. This makes it difficult to compare one type of management to another, to mistake two different entities with vaguely similar presentations for the same condition, and to make each new patient the sole enrollee in her own clinical trial.
(next, in part 6: endometriosis, polycystic ovarian syndrome and the journey from analog to digital gynecology)