1/ n As promised, a quick thread. Combination of my (non-PhD / layman's) dive into learning about Monoclonal Antibodies and how it's helped me uncover a few fun / interesting group of companies: $SDGR $ABCL $TWST $IPA (new QQQ uplist -formerly $IPATD) and most recently $LGND

Ok - first, a *quick* history lesson - in the last ~3 months, I have been increasingly obsessed w/ learning about monoclonal antibodies. It started as a simple pattern recognition that a lot of the biotechs I was investing in were in this space - $HGEN $PRVB $MGNX $ONCT etc.
Not to mention, all of these new COVID therapeutics ( $LLY $REGN ) were antibody based - what the heck exactly are these things? I found myself watching basic videos - like this simple 3 minute cartoon summary... https://t.co/aJPVqCTMTH
.. to this podcast on the history of monoclonal antibodies, like this Nature podcast: https://t.co/iXcq56RR5l And a bunch of more academic / scientific white papers and articles that are far too dry to share here
Probably a good time to add that I barely made it past high school biology - my academic and professional background is all based around finance / math / SaaS - so as much as I'm interested in biotechnology, it's all self-taught and I needed to start with the basics
Anyways - the overly simplistic takeaway I came away with was that we know antibodies are capable of curing / reducing LOTS of diseases. But in 2020 we are now faced with a near infinite supply (of antibody combinations) and the constraint is around discovery and testing
Playing a role in speeding up the "time to fail" and identifying "signal through the noise" part of drug discovery process can shave years / maybe even decades of bringing a drug to market - this is very, very valuable stuff.
Quick side plug for a super fascinating video on DeepMind's entrance into this arena with AlphaFold: https://t.co/gvRFnDzYuK This is really, really cool stuff and as seen by the DeepMind teams progress in 2020 -we're starting to hit an inflection point.
Anyways - back to antibodyAntibody Drug Discovery - two basic sides of the equation here 1) Production and Cataloguing - the sourcing and manufacturing of the antibodies - think the raw materials / "spice shelf" equivalent and 2) Manual or Computational Modeling and Testing
Upstream from the clinical trial phase (which preceeds the commercialization phase) pre-clinical / drug discovery is critical to creating an essential "Top of the Funnel" pipeline for new and innovative drugs
This is where companies like Schrodinger $SDGR Ligand $LGND Abcellera $ABCL Immunoprecise $IPA and Twist $TWST - as I come across new companies, I am building out a basket of what you might call the "21st Century Pick and Shovel" companies of biotech drug discovery
I like this arena because it's less of a binary bet on any single drug or company's ability to execute and more of a way to directly play the macro theme of Biotech coming into a new golden era of rapid drug discovery and development
Some of these companies get more attention than others, but I have found all of them have overlapping business models / IP / and partnerships - many of them are even partners with each other. $IPA for example is a partner of both $LGND & $TWST - $TWST + $SDGR are partners, etc.
Many of them have realized that they are sitting on goldmines and treasure troves of data themselves and have begun the process of bringing some of the development efforts in-house - $SDGR spun off $MORF , $IPA has Talem Therapeutics, etc.
$LGND which I was diving into last night has multiple different business units focused on top of funnel drug disocvery - OmniAb is the antibody production and discovery side of the house - which based on my past research into $IPA and $ABCL is what originally caught my eye
This asset-light "upstream focused" model allows them to focus on the science (& partnerships) & take on very little risk from a capital-outlay perspective - as you see below, we've got a business that I believe is starting to hit it's stride in 2021 w/ many shots on goal
Capisol is a biz unit that produces a key ingredient to many late-stage clinical and approved drugs - including Remdesivir w/ Gilead $GILD . One trick pony you ask? Not so fast - Contract revenue broke out in Q4 - and take a look at their partners page: https://t.co/qeszYOYeK6
So little known Ligand now has over half a billion dollars in cash w/ no debt, just acquired a *very* interesting asset in August with Pfenex for ~$500m, and over 60% of the shares borrowed short - catalyzed by an old 2018 Citron short report. Very thin name only 15m shares float
If the Ligand is able to do a better job of telling their story: the crucial role they play in drug discovery, the massive pipeline they are building, and additional approvals in 2021 help build confidence in their biz model and IP - stock could trade significantly higher
I am adding Ligand to my "Pick and Shovels" play on biotech innovation via antibody production and computational discovery - also to my portfolio along with $IPA - $ABCL $SGDR and $TWST will remain on my shopping list for the next market pullback.
Anyways, thats enough for one thread... hope some folks found it interesting! By no means an expert here as the cartoon youtube video hopefully shows - very open to sharing of additional related content or reading, questions, other interesting companies to dig into in this space

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I'm going to do two history threads on Ethiopia, one on its ancient history, one on its modern story (1800 to today). 🇪🇹

I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):


The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹


Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹


References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹
I just finished Eric Adler's The Battle of the Classics, and wanted to say something about Joel Christiansen's review linked below. I am not sure what motivates the review (I speculate a bit below), but it gives a very misleading impression of the book. 1/x


The meat of the criticism is that the history Adler gives is insufficiently critical. Adler describes a few figures who had a great influence on how the modern US university was formed. It's certainly critical: it focuses on the social Darwinism of these figures. 2/x

Other insinuations and suggestions in the review seem wildly off the mark, distorted, or inappropriate-- for example, that the book is clickbaity (it is scholarly) or conservative (hardly) or connected to the events at the Capitol (give me a break). 3/x

The core question: in what sense is classics inherently racist? Classics is old. On Adler's account, it begins in ancient Rome and is revived in the Renaissance. Slavery (Christiansen's primary concern) is also very old. Let's say classics is an education for slaveowners. 4/x

It's worth remembering that literacy itself is elite throughout most of this history. Literacy is, then, also the education of slaveowners. We can honor oral and musical traditions without denying that literacy is, generally, good. 5/x
हिमालय पर्वत की एक बड़ी पवित्र गुफा थी।उस गुफा के निकट ही गंगा जी बहती थी।एक बार देवर्षि नारद विचरण करते हुए वहां आ पहुंचे।वह परम पवित्र गुफा नारद जी को अत्यंत सुहावनी लगी।वहां का मनोरम प्राकृतिक दृश्य,पर्वत,नदी और वन देख उनके हृदय में श्रीहरि विष्णु की भक्ति अत्यंत बलवती हो उठी।


और देवर्षि नारद वहीं बैठकर तपस्या में लीन हो गए।इन्द्र नारद की तपस्या से घबरा गए।उन्हें हमेशा की तरह अपना सिंहासन व स्वर्ग खोने का डर सताने लगा।इसलिए इन्द्र ने नारद की तपस्या भंग करने के लिए कामदेव को उनके पास भेज दिया।वहां पहुंच कामदेव ने अपनी माया से वसंतऋतु को उत्पन्न कर दिया।


पेड़ और पौधों पर रंग बिरंगे फूल खिल गए और कोयलें कूकने लगी,पक्षी चहकने लगे।शीतल,मंद,सुगंधित और सुहावनी हवा चलने लगी।रंभा आदि अप्सराएं नाचने लगीं ।किन्तु कामदेव की किसी भी माया का नारद पे कोई प्रभाव नहीं पड़ा।तब कामदेव को डर सताने लगा कि कहीं नारद क्रोध में आकर मुझे श्राप न देदें।

जैसे ही नारद ने अपनी आंखें खोली, उसी क्षण कामदेव ने उनसे क्षमा मांगी।नारद मुनि को तनिक भी क्रोध नहीं आया और उन्होने शीघ्र ही कामदेव को क्षमा कर दिया।कामदेव प्रसन्न होकर वहां से चले गए।कामदेव के चले जाने पर देवर्षि के मन में अहंकार आ गया कि मैने कामदेव को हरा दिया।

नारद फिर कैलाश जा पहुंचे और शिवजी को अपनी विजयगाथा सुनाई।शिव समझ गए कि नारद अहंकारी हो गए हैं और अगर ये बात विष्णु जी जान गए तो नारद के लिए अच्छा नहीं होगा।ये सोचकर शिवजी ने नारद को भगवन विष्णु को ये बात बताने के लीए मना किया। परंतु नारद जी को ये बात उचित नहीं लगी।