Sometimes it is easy to forget that your job and your career are two different things. Your job is what you do for your employer. Your career is the path that will get your through a sequence of jobs to achieve your personal goals. Your career will be influenced by events outside of your control, like life events or the economy, but you do have some control over your career and you should use it.
A few weeks ago I gave a presentation on this topic to the CS Seniors at CSUM – Cal State University Monterrey Bay – as part of a series on Life After College. The short summary of the presentation was:
Your Job is not your Career – You are in charge of your Career,
Software is a key part of BioTech,
You should consider adding BioTech to your career Choices.
During the presentation I used as an example Freenome, an early stage BioTech company that I joined at the end of 2020 after spending most of my career in HiTech.
I re-recorded the presentation into a 9 minute video that you can see HERE.
The acquisition of Sun Microsystems by Oracle Corp closed 11 years ago, on Jan 27th, 2010, 9 months after it was first announced.
I had been at Sun for many years and I really liked what I was doing but, in hindsight, the acquisition forced me to accept change, and that was good. I stayed at Oracle for a few months, and then left for BlackBerry (then RIM) where I joined other ex-Sun people, learned new things and shared some of what I had learned with new colleagues in a different community.
I believe that embracing change, and exchanging communities, is a key asset in our industry. We learn new things through experimentation and observation, and then reshuffle and try again in a new environment. And, collectively, we move forward.
I reported on the beginning of the Sun exodus a year after the acquisition: people and OSS projects. The process has continued, though I have only tracked the movement through my direct friends. On a personal level, after BlackBerry I joined Progress, and then CloudBees.
Cancer sucks and I believe I can help Freenome in its mission.
I can learnnew things: Biology, ML, Workflows, Python, Continuous Improvement in a Regulated Industry, and many other topics
The company culture is outstanding
The change to Freenome is arguably the biggest change so far for me, from hiTech to bioTech. This change enables many opportunities for learning and teaching across these two industries, and I will write about that in the future but, in the meantime…
Change may sometimes be scary but, change is good! My lesson is to embrace it and keep growing…
And ping me if you are considering a move to BioTech. Particularly if Freenome has any appeal to you.
The current lack of an effective, blood-based test may be a contributing factor to low rates of CRC screening today, with nearly 1 in 3 adults aged 50-75 years non-adherent with screening guidelines. Existing methods, such as colonoscopy and stool-based testing, are often seen as inconvenient and uncomfortable by patients, leading many to postpone or forgo recommended screenings
A concise description of the value of a blood-based screening for CRC.
We have shown that it’s possible to take a machine learning–based approach to decode the relationship between a patient’s cell-free DNA profile and his or her cancer status, detecting CRC in our dataset with a top performance of 82% sensitivity at 85% specificity. These are very encouraging data that support the continued development of a CRC screening test that includes cfDNA and machine learning as key components.
Above is a quote from Freenome’s Chief Medical Officer, Girish Putcha. Sensitivity is a measure of how well the test can identify true positives, while Specifity is a measure of how well the test can identify true negatives (see Wikipedia). There is a trade-off between sensitivity and specificity and, as indicated in public reports elsewhere one of the key benefits of the Freenome approach is that we can tune the tradeoff depending on the cancer and the treatments.
Freenome’s multiomics blood test can detect early-stage colorectal cancer (stage I/II) at 94% sensitivity and 94% specificity.
The improved sensitivity and specificity above numbers reflect advances since the earlier results reported in Oct 2018. The test reported here combines cell-free DNA (cfDNA) as well as protein biomarkers into a machine-learning classifier.
Following strong data presented at ASCO-GI … we are initiating the pivotal trial for our blood-based CRC test
Initiation of the CRC Clinical Trial
PREEMPT CRC is Freenome’s prospective clinical trial that will enroll 14,000 individuals to validate its multiomics blood test for CRC screening and FDA approval. The study will include asymptomatic, average-risk patients between the ages of 45 and 85 undergoing a screening colonoscopy.
multiomics blood test can detect colorectal advanced adenomas at 41% sensitivity and 90% specificity,
Concise description of the result.
The data from a pre-defined subset of AI-EMERGE® (n=522) showed that Freenome’s novel multiomics blood test for colorectal cancer screening was able to detect colorectal advanced adenomas (AAs) with a sensitivity of 41% at a specificity of 90%. Compared with the FDA-approved mSEPT9 (methylated septin 9) blood test, Freenome’s multiomics blood test showed much higher sensitivity (41% vs. 22%)1 for detecting AAs. When compared to currently available stool-based tests, the test demonstrated much higher AA sensitivity than a fecal immunochemical test, or FIT (41% vs. 24%) and comparable AA sensitivity to FIT-DNA (41% vs. 42%)2
And more details. Note that, unlike the report from 2020, this one is reporting on Advanced Adenomas, i.e. pre-cancer.
The technology stack is mostly Python in the back-end, on K8s and GCP (et al.), and React in the front-end. I’ll provide more insight as I ramp up in 2021 but you can look at the openings in the Freenome career’s page. There are two relevant groups of openings, one for Computational Science and one for Engineering – I am in the Engineering group, and I’d expect most of my friends/contacts to be in that area but look around. The core approach is multiomics, using molecular biology and machine learning to detect cancers in blood, so regardless of where you land, Freenome would give you an opportunity to learn about those two areas.
The company’s HQ is in South San Francisco, in the Verily campus which includes the usual Alphabet goodies. We are all working from home right now, and there is some remote work flexibility.
Today (Dec 28th), I started at Freenome. Freenome is developing and productizing a Multiomics platform for early cancer detection. The tag line is “Spot the pattern, treat the cancer“. Multiomics means doing analysis on data from multiple “omes“, i.e. using fragments of DNA, RNA, proteins and other biomarkers from blood plasma. The first study is PREEMPT CRC – Colorectal Cancer.
I am joining as an Engineering Manager, same role as what I had at CloudBees. The technology platform is mostly Python in the back-end, plus JS in the front-end, plus… I’ll find out.
I’m very excited to join Freenome. I liked the team and the company, and loved the mission! I’ve lost multiple friends and relatives to Cancer, and I myself had an early encounter with Prostate Cancer, so any little thing I can do to help, sign me in!
Freenome is located in South San Francisco, close to many other BioTech companies, and has a strong list of partners and investors. In the short-term, I will be working from home – like everybody else.
I left CloudBees last month. It was a great journey. We started with a basic concept, a very small team and somewhat limited experience with modern SaaS. We ended with two multi-featured products (DevOptics and SDM), on AWS and GCP, in a multi-region team, releasing in a CI/CD workflow using a very modern stack. We all learned a lot about technology and processes.
And great people! Smart, kind, team players, with many accents and cultures distributed all over. In the US we had people in the West (CA, OR, WA) and East Coasts (PA, MA, NC, FL) – and Texas, let’s not forget Texas! Outside the US, we had people in Australia (yep, 6 hours behind me) Ireland, Scotland, and England, Spain, France, Austria, Switzerland, (that’s CET for you, 9 hours ahead of me), and briefly Croatia (that’s 10 hours ahead!) – I became fairly good at Time-Zone math 🙂 And I learned about Irish and Australian sense of humor…
Thanks to everybody that shared this journey with me; do stay in touch.
CloudBees was great but it was time for me to move on.
I took a short break between jobs but I start at my new job tomorrow. More about it tomorrow!
Hot off the press: you can now model your value stream and track your deployment frequency using the Free Plan for CloudBees DevOptics. We released this new functionality as part of the ramp-up to next week’s DevOps World | Jenkins World San Francisco. There are two main new aspects: an improved, and free, value stream modeler, and extending the availability of deployment frequency available to the Free plan.
With the stream modeler you can capture how software flows through your system (or you can design how you want it to flow) by creating and connecting Gates. Then, if your flow is based on jobs running on Jenkins or CloudBees Core CI/CD masters, you can connect these gates to the jobs using the DevOptics Plugin and leverage the computational aspects of CloudBees DevOptics.
The connected masters need to be configured to a DevOptics account, either in a Free plan or in a Premium plan. Both plans provide CD platform monitoring (Run Insights) – the Free plan only provides 7 days of statistics while Premium extends that to 90 days. The Free plan now also provides Deployment Frequency metric for all gates, albeit also only for 7 days. The Premium plan adds two more Job-based metrics: Change Failure Rate and Mean Time to Recovery as well as Mean Lead Time. Mean Lead Time is based on Value propagation in the form of commits and tickets through your Value Stream, which is a key feature of DevOptics Premium.
Using the Value Stream modeler is straight-forward. Setting up the plugin to enable Deployment Frequency is pretty easy too but below I spell out the steps, starting right after my earlier post: Upgrading to the latest DevOptics…
After connecting the plugin go to the Settings creen in DevOptics This is how it looks if you have configured only have Run Insights section of the Plugin:
And this is how it looks after connecting also the Value Streams section:
Now create your value stream:
Here is a very simple one-gate value stream
If we leave the gate unconfigured, it will look as this (note the wrench icon):
But, since we want to track Deployment Frequencies, we will now edit and configure the gate against one of the jobs in a master where a plugin has been installed. This is the configuration popup:
Save and you will see that the wrench goes away:
At this point we are ready! We just need to run some jobs on the master and data will flow, so…
We go to our Jenkins and run some jobs…
Now if we go back to the DevOptics app and look at the Value Streams screen we will see something like this:
On the Run Insights side, the graphs will initially look as below – note that the grey bars are gone and there is some empty space for the most immediate time interval:
But, if we wait a bit for the data to be propagated, we will see:
DevOps World | Jenkins World SF is around the corner, so time for an update post to add to the collection of posts on DevOptics … et al.
Back in September 2018 I posted instructions on how to install your Jenkins distribution from scratch, and then how to install the DevOptics Plugins. Let’s assume you had done that, so, picking up from there…
The first step would be to install the latest version of Jenkins. Since I already had one, I just accepted the request from within Jenkins and installed the new version. That got me from 2.121.3 to
Next was to upgrade the DevOptics Plugin
By now I was running a fairly old version, I jumped from 1.1349 to 1.1739
The upgrade went pretty smoothly, and I restarted. Then I went to look at the Connectivity status of the DevOptics Plugin. Here, the latest Plugin is trying something different: it is asking me if I want to enable the Value Stream functionality. Here is the screenshot:
The Value Stream functionality depends on additional plugins. I can continue as-is, without installing the extra dependencies, or I can install the recommended plugins. I chose the latter, and then I reinstalled.
I knew that my DevOptics subscription had changed recently, so, partly as an exercise, I disconnected the plugin and then reconnected. This is the popup we get on disconnect
And this is the message we get on reconnect:
Cool. Now I am back to where I was, except that now the new dependencies have been installed and my DevOptics plugin is fully connected.
At this point we are cooking and the Plugin should be connected to the back-end. Stay tuned for the next post in this series.