Decompressing snapshot · ClinicalTrials.gov v2 · Drugs@FDA
SAROSFY26–28gcarosso.bio ↗
snapshot

Catalyst timeline

primary-completion dates by month · click a bar to focus · December and June spikes are sponsor placeholder estimates, discount them

Readout calendar

Sponsor league table

lead sponsor · trials in window, stacked by phase · click to filter

Program profile

select a sponsor

Concentration

Venture-backed longevity companies — clinical presence

87 companies compiled from public reports, July 2026 · matched to registered 2026–28 readouts by sponsor name

Capital by company status

total raised, US$ m · shaded = has a registered 2026–28 readout

Aging-adjacent trials, all sponsors

mechanism / indication keywords: senolytic, mTOR, NAD⁺, sarcopenia, frailty, healthspan, reprogramming…

Therapeutic area × phase

count of trials · hover for enrollment and readout share · click to filter

Area by readout quarter

Phase 3 only

Enrollment mass by area

sum of planned/actual enrollment

Modality mix

derived from intervention names and keywords

Modality × therapeutic area

Modality readout cadence

Phase 3 primary completions per quarter

Site footprint by country

trials with ≥1 site in country

Sponsor domicile signal

heuristic from lead-sponsor name

Regulatory calendar

PDUFA, AdCom and resubmission dates as disclosed in SEC filings · each row cites its filing

FDA approval actions

Drugs@FDA submissions with status Approved · 2025 → present

Readout-confidence distribution

heuristic score, Phase 3 in window

Signals

Highest-conviction Phase 3 readouts next 180 days

confidence ≥ 75 · sorted by date

Data provenance

Method notes

Universe. Interventional studies with an industry lead sponsor whose primary-completion date falls in calendar 2026–2028, Phase 1 through Phase 3, as registered on ClinicalTrials.gov. The default window is the current month through Dec 2028, the whole registered universe; narrow it in the rail. Registered dates lag real readouts: open-label early-phase programs routinely read out interim data a year or more before the registered date. Dates are sponsor-estimated unless flagged ACTUAL; month-precision dates are placed on the 15th.

Trial health. Enrollment per month is registered enrollment divided by months from study start to primary completion. That span includes follow-up, so it is a schedule-density proxy, not observed recruitment velocity; a low value flags a record to check, not a recruitment problem. Site density is sites per 100 patients. Both are compared with the median of trials in the same area and phase in this universe. A study below half its peer median loses six confidence points unless it is completed or reports an actual date.

rNPV sketch is a deliberately simple model — linear ramp, flat plateau, three-year erosion after exclusivity, single discount rate, one cost-to-complete number — pre-filled from the registry, the literature prior and SEC cover-page share counts. It exists so a number can be stress-tested in the dossier, not to replace a proper model.

Readout confidence is a transparent heuristic, not a model fit: it rewards actual (vs. estimated) completion dates, completed or active-not-recruiting status, actual enrollment counts and recent registry updates, and penalises not-yet-recruiting status, stale records and stopped studies. Use it to triage, not to price.

Flags. Each trial carries the first rule that fired for it, shown with its trigger: stopped → Stopped; cash months < months to primary completion → Cash flag (cash binding; the row says when the test is not applied: large pharma, positive operating cash flow, or no SEC financials); completion date passed, estimated inside 90 days, or slipped → Date passed / Date unconfirmed / Date slipped; ≥2 specialists new last quarter → Specialist adds; an insider buy cluster inside 180 days → Insider buys; enrollment density below half the peer median → Enrollment lag; Phase 3 with an actual registry date and confidence ≥75 → Pivotal, actual date; other Phase 3 inside 6 months → Pivotal inside 6 mo; else No flag. These are descriptive labels for triage; none is a position recommendation, and their false-positive rates are not yet measured (see the roadmap’s evaluation phase). Date reliability is firm (the registry reports primary completion as ACTUAL, i.e. data collection for the primary endpoint has ended; it says nothing about when results are announced), estimated (registry estimate), or slipped (primary completion pushed out by a month or more since the previous weekly snapshot, unless the move was off a June/December placeholder or onto an actual date — that is a firming). A slipped date is a Wait: the registry just said the plan changed. Impact = phase weight × (0.5 + literature prior) × size factor (log public float) × firmness × crowding discount, bucketed High ≥0.62 / Med ≥0.35 / Low. It ranks how much attention a readout deserves in an investable universe: the size factor rewards a liquid, listed sponsor and is not a claim about how far the stock would move — a pivotal readout at a micro-cap can matter far more to that equity. Cash-to-event uses the runway above: cash plus every investment tag the filer uses (current and non-current marketable securities, available-for-sale and held-to-maturity debt), from the company’s own XBRL facts at one balance-sheet date, over operating cash outflow annualised from the latest year-to-date figure in the same filing; the fiscal-year figure and then the annualised net loss are fallbacks, each labelled in the dossier. Debt is shown beside cash and is not netted from it; a sponsor whose reported operating cash flow (or, failing that, net income) is positive is treated as unconstrained, and missing inputs are shown as unknown rather than zero. All of it is rules, none of it is advice.

Snapshot diff. Each weekly build is compared with the previous one, trial by trial: primary-completion date (with the size of the move in months), estimated → actual, status, enrollment and why-stopped. Slipped, Date firmed and New this snapshot are filterable flags in the rail; the dossier lists the raw before → after values, and each build's diff is kept under data/history. Registry dates lag real readouts, so a single slip mostly confirms what the market has priced; the second slip is the signal.

Base-rate priors are phase-transition probabilities from Wong, Siah & Lo (2019, Biostatistics), oncology vs. non-oncology, shown for context only. The prior column is the single next-step transition (e.g. Phase 2 → Phase 3); the rNPV sketch is pre-filled with the cumulative probability of approval from the current phase, the product of the remaining transitions, which is a different and smaller number for early-phase programs. Both are population averages and say nothing about a specific asset.

Therapeutic area and modality are assigned by pattern-matching titles, conditions, keywords and intervention names. A registered intervention type of DRUG with no recognisable name or class stays Drug (unclassified), about half the universe, rather than being called a small molecule. Expect a few percent mis-assignments among the classified ones; the dossier shows the raw fields so you can check.

Sponsor tier. "Large pharma" is a fixed list of ~25 groups with subsidiaries mapped (e.g. Genentech → Roche, Janssen → J&J). "China-domiciled" is inferred from corporate suffixes and city names in the registered sponsor string.

FDA actions come from the openFDA Drugs@FDA endpoint. It covers approval actions on NDAs/BLAs/ANDAs, not target dates, which the FDA does not publish.

Regulatory calendar. PDUFA target dates, advisory-committee meetings and planned resubmissions are read from the companies' own SEC filings: EDGAR full-text search over 8-K, 6-K, 10-Q and 10-K documents and their press-release exhibits for the trailing 24 months, refreshed weekly on the trailing three weeks. Each date is classified from its own sentence, carries day, month or quarter precision (≈ marks a period-end placeholder), and cites the filing it came from; when a later filing states a different date the earlier statement is kept as history and the row is marked moved. Confidence is firm for an exact date in a filing under six months old and guided otherwise. Filers are resolved to tickers by CIK. Coverage trails a paid calendar for companies that only say the date on a call or a slide, and a date inside an image exhibit is invisible to text search. Market cap is the last close times cover-page shares outstanding where a quote is available (Yahoo chart endpoint, Nasdaq quote API as fallback; unofficial, dated in the dossier); otherwise the SEC-reported public float, marked “f”.

Private companies. Sponsors with no SEC equity match — about two thirds of the universe: private companies, unlisted subsidiaries, ex-US listings and names the join cannot resolve, which the dashboard does not tell apart — are resolved by name (current and previous legal names) to SEC Form D issuers in the Biotechnology and Pharmaceuticals industry groups, which gives Regulation D placements since 2019: amount sold per notice, offering size, investor count, and the officers, directors and promoters named on the filing. NIH RePORTER supplies non-dilutive awards by organisation name for the venture-stage tail and for the longevity companies, most of which are pre-IND and absent from ClinicalTrials.gov. Neither source contains valuations, terms, cap tables, burn or board seats; those are stated as unknown rather than estimated.

Programs & peers. The sponsor, not the trial, is the unit of analysis: each program is a vector over area × phase × modality, and peers are the sponsors with the highest cosine similarity on that vector. Trials are coordinates, not oracles — the peer set is how a readout should be read.

Specialist ownership. Latest two 13F-HR information tables for a fixed list of biotech-specialist managers (Baker Bros, Perceptive, RA, OrbiMed, Deerfield, Redmile, Avoro, EcoR1, Logos, Cormorant, Boxer, Vivo, Frazier, Rock Springs, Braidwell, Commodore, Darwin, Paradigm, Bain LS, Vestal Point, Samsara, TCG Crossover, Ally Bridge, Sofinnova, Sectoral, Tang, BVF); multi-strategy managers such as Point72, Viking, Woodline and Polar are deliberately excluded because their books dilute the signal, aggregated by issuer and matched to sponsors by name. This is the "specialist consensus" quality signal; count of holders matters more than dollars, and a 45-day lag applies.

Insider activity. Open-market purchases and sales (Form 4 transaction codes P and S) from the SEC's quarterly insider-transactions data sets, aggregated by issuer over the last two published quarters and joined by issuer CIK or ticker. The current quarter is not yet published, so the window ends at the last quarter-end. FINRA consolidated short interest is shown where the public feed responds.

Longevity companies. Names compiled from public reports (July 2026) are matched to lead-sponsor strings; aging-adjacent trials are flagged by mechanism and indication keywords across all sponsors. Capital raised is as publicly reported and is not re-verified here.

Company-guided milestones. Sentences in 8-K and 6-K filings (trailing 120 days, EDGAR full-text search) in which a company gives a period for topline data, an interim analysis, enrollment completion or a study start: "topline data in the second half of 2026". Each row keeps the sentence, the period precision (day, month, quarter, half, year) and the filing. They are the company’s own dates, shown beside the registry date and never merged with it; a period is placed at its end. Boilerplate (forward-looking statements) and PDUFA sentences are excluded, the latter because the regulatory calendar already carries them.

Registry versions. For every trial whose record changed since the weekly baseline, the dashboard fetches the ClinicalTrials.gov version list and shows the versions saved since then with the modules the sponsor edited. The snapshot diff also compares the primary-outcome text, so a changed endpoint shows its before and after; an edit to the outcome module alone is reported as an edit, not as an endpoint change.

Daily delta and the changes feed. A daily job re-pulls the registry, the regulatory calendar, filings and prices against the Monday baseline; the weekly job rebuilds everything. What moved is published as changes.json and changes.xml (RSS) beside the app: slipped, firmed and new trials, status changes and moved PDUFA dates, each linked to its record. The in-app change log reads the same list.

Live refresh queries the ClinicalTrials.gov v2 API for records updated since the snapshot and merges them in place; the status bar then shows the merged count separately from the weekly snapshot diff. It works from saros.gcarosso.bio and from the local file; a host that sandboxes outbound requests (such as an embedded artifact viewer) reports the block instead.

About SAROS

what it is, how to read it, where the numbers come from
SAROS mark
SAROS
A navigator of today's clinical trial landscape, mapped to the money around it. Its horizon spans 2026–2028. Public sources only. Registry, filings and prices refreshed daily; full rebuild weekly.

What you can do here

  • See what reads out when. The timeline and calendar hold 10,000+ Phase 1–3 trials by registered primary-completion month. Narrow by phase, status, area, modality, sponsor tier, target or enrollment from the left rail; click any bar, cell or sponsor to focus on it. Clear all at the top of the rail resets everything.
  • Open any trial's dossier by clicking its row: the flag that fired and its rule, readout confidence with its reasons, cash and runway against the date with the filing period named, filings since the balance sheet, who holds the stock, insider trades and short interest, the dates the company itself has guided to, the drug's mechanism with a curated note, an editable rNPV sketch, and every competing trial in the same indication.
  • Search by target. Type KRAS, GLP-1 or CD19 in the rail box or in ⌘K and the whole dashboard filters to trials tagged with that mechanism.
  • Check the FDA calendar. The FDA tab lists PDUFA, advisory-committee and resubmission dates exactly as companies disclosed them in SEC filings, each with a link to the filing and the sentence it came from. Dates that moved keep their history.
  • Look inside private sponsors. Roughly two thirds of sponsors have no SEC equity match — private companies, unlisted subsidiaries, or names the join cannot resolve. Where they have filed Regulation D placements, the dossier shows amounts raised, dates, investor counts and the named officers and directors; NIH awards show non-dilutive funding. The Longevity tab carries the same for venture-backed longevity companies.
  • Read a sponsor as a program. Programs & peers profiles a sponsor across every area and phase and lists the sponsors whose programs look most alike, plus which specialist funds crowd into it and where insiders are buying in clusters.
  • Open a company. Click any ticker for one view per listed sponsor: programs by primary completion, cash with its period and the tags behind it, debt, filings since the balance sheet, holders, insiders, short interest, regulatory dates, and the milestones the company has guided to in its own filings.
  • Track what changed. The registry, regulatory dates, filings and prices are re-pulled every day against Monday's snapshot. Slipped, firmed and new trials are filter flags; the dossier shows the before and after, primary-outcome text included, and the registry versions the sponsor saved since. The same list is published as an RSS feed at /changes.xml.
  • Keep a book. Star trials (★ or W) and the Book preset turns the home page into your watchlist with 7/30/90-day catalyst counts. Export any view to CSV.

Start with a preset

Also in the top bar

  • Sector — the case for and against biotech as a sector, with the published evidence redrawn as charts.
  • Visuals — one page of overview charts across the whole snapshot, all click-through.
  • Method tab — how every score is built and the exact query and pull date behind every number.

Keyboard

⌘K search trials, targets, sponsors, indications, investors   ⇥ next tab   W star the open dossier   J/K next / previous row   esc close

Why "SAROS"

A saros is the cycle of 18 years, 11 days and 8 hours after which the Sun, Earth and Moon return to the same alignment, so an eclipse repeats with nearly the same geometry. Babylonian astronomers found it by keeping a long, honest ledger of dates; by the time of Thales it could be used to say when the next eclipse would come, without any theory of why.

That is the stance taken here. A trial readout is a scheduled alignment: a registered date on which a company, a drug and a market meet. This page does not predict the outcome; it keeps the ledger of when those alignments fall, what is known about each party, and how the dates drift from one week to the next. The eclipse in the mark is the moment of the readout, and the moons beneath the timeline are the calendar it runs on.

How to read a row

  • Primary completion — the registered primary-completion date, not the announcement of results. A means the sponsor reported it as actual. A coloured month badge means it moved since last week. June and December pile-ups are sponsor placeholders; treat them as "sometime that half".
  • Conf. — readout confidence, 0–100, a transparent rule score of whether the date will hold. Use it to triage, not to price.
  • Prior — the historical share of trials at this phase that advance (oncology vs non-oncology). A base rate, not a view.
  • Impact / Flag — how much a readout could matter, and the first rule that fired for the record (Stopped, Cash flag, Date passed, Date unconfirmed, Date slipped, Specialist adds, Insider buys, Enrollment lag, Pivotal). Hover a value for the rule.
  • Mkt cap — last close × shares outstanding where a quote is available (dated, unofficial source named in the dossier); otherwise the SEC public float, marked “f”.
  • Boxes that change the view carry an orange corner tab; boxes without one are just numbers. Hover any control, column header or score for a plain-language explanation.

Sources, definitions and limits

Every number here comes from a public source and the Method tab lists each one with its cadence, the join used and the exact query and pull date. How the scores are defined, what a registered date does and does not mean, and where the tool stops are written up once, on the standalone method page. In one line: registered dates lag real readouts, private valuations and terms are shown as unknown rather than estimated, and paid data is out of scope by design.

Sector

the case for biotech versus other sectors, and the case against — distilled from Verdad's Biotech Investing (Obenshain, Rasmussen & Wintner, 2025); charts redrawn from the paper's published values
Twenty-year return to 2019
9.3% vs 6.1%
S&P Biotech vs S&P 500, annualised
Correlation with other sectors
0.32
lowest of twelve sectors
Companies in the index
400+
~11% of the S&P Total Market · most of any sector
After prior relative drawdowns
+63%
average 2-year return vs market · 4 episodes

Why the sector eight arguments, each with the evidence behind it

1 · It has paid, in aggregate

For the twenty years before 2020 the S&P Biotech Index returned 9.3% a year against 6.1% for the S&P 500 and 7.6% for the Russell 2000. The return comes from a few acorns that grow into oaks; they pay for a morass of failures (see the cautions below).

2 · It diversifies a book

Because outcomes hinge on science and on big-pharma acquisitions rather than the business cycle, biotech's average correlation with every other sector is 0.32, below any other industry pair. In portfolio terms, that is the scarcest property a sector can have.

3 · Names inside it do not move together

Average pairwise correlation of 12-month returns within the sector is 0.25, second-lowest of twelve. Diversification inside biotech buys more risk reduction than inside other industries, provided the risk model is trained on biotech-specific data.

4 · The breadth is in small caps

Biotech is a sliver of the largest 500 companies but over 20% of the smallest. More than 400 index names, more than any other sector, give a quantitative approach the numbers it needs, and most of them sit where specialists have the biggest edge and the biggest funds cannot go.

5 · Expertise is measurable from public filings

Sort biotech stocks by how heavily specialist funds own them (13F), by the bullishness of insider trades (Form 4), or by short interest, and each spreads returns from the bottom quintile to the top: −2% → +20%, 0% → +15%, and −19% → +16% annualised. These are the three quality signals SAROS carries into every dossier.

Specialist-fund concentration
Insider trade signal
Short interest (1 = most shorted)

6 · The usual factors break; biotech-specific ones work

Traditional momentum (a stock's own trailing return) does nothing, and traditional value (profits to enterprise value) runs backwards because most of the sector has no profits. Redefine them on the sponsor's program: momentum of the closest scientific peers, and value anchored on spending rather than profit, and both spread returns. Blend value, specialist quality and peer momentum and the spread runs from −17% to +21%.

Momentum · traditional vs peer-based
Value · profit-anchored vs spending-anchored
Blended factor model, quintiles
Value still works inside each specialist-concentration group (annualised)
Specialist concentrationExpensiveFairCheap
Low-3%+7%+5%
Medium-3%+6%+7%
High+7%+9%+13%
rows = specialist concentration · columns = spending-anchored value; cheap and specialist-held is the best cell, expensive and specialist-spurned the worst

7 · Long and short is what makes it investable

With this many losers, shorting is the least explored and most important tool. A weekly-rebalanced long/short portfolio at 20% target volatility, net of trading, execution and borrow costs, returned 19.1% a year with a 32% maximum drawdown; the XBI did 3.7% with a 64% drawdown over the same 2015–2025 window.

Ann. returnAnn. volReturn / volMax drawdown
Long/short backtest19.1%18.9%1.01-32%
XBI3.7%33.2%0.11-64%
S&P 50013.3%18.1%0.74-34%
Jan 2015 – Aug 2025 · constraints: 5% max long, 2% max short, 200% gross; realised 124% long / 73% short

8 · The cycle: winters end

Biotech has lagged the S&P 500 since 2019 and sits in its deepest relative drawdown on record. After the four comparable episodes it returned +63% versus the market over the following two years on average. Meanwhile the supply side is strong: a ~$200B patent cliff by 2030 forces pharma to buy revenue, and approvals have run at or above 50 in five of the last seven years, 72% of 2024's from small and mid-sized companies.

TroughDrawdown vs S&P+1 yr+2 yr+3 yr
Aug 1989-76%37%163%125%
May 1995-77%55%20%-23%
Jun 2007-79%30%38%31%
Feb 2011-62%18%33%113%
Dec 2025-117%———
Average35%63%61%
CDER novel drug approvals, 2015–2025

What can go wrong the same paper, read from the other side

Most biotechs lose money

Of the ~1,000 biotechs that ever reached $200M of market cap since 1996, 67% delivered a negative lifetime return; the median company compounded at −15% a year against +1% for the median US company. Half of the losers were acquired at a loss, a tenth were delisted, and the rest are still listed, many below their cash: stranded capital that was never returned.

Where the ~1,000 companies ended up

Following the experts does not remove the risk

The top quintile of specialist ownership beats the XBI, but it is 82% correlated with it: 29% annual volatility for both, and a 61% maximum drawdown against the ETF's 57%. Return, yes; risk reduction, no. That is why argument 7 needs the short book.

CorrelationAnn. volMax drawdown
Top-quintile specialist names82%29%−61%
XBI—29%−57%

The edge is regime-dependent

Specialist-following earns almost all of its excess return in calm markets, a third of the time. In medium and high-volatility months it does no better than the index.

Average monthly return by VIX level

Conventional playbooks invert

Cheap-on-profits is the worst quintile, expensive the best; own-stock momentum is flat to negative. A generalist screen, applied here, selects the wrong side of both. The factor charts in argument 6 are the evidence; the practical consequence is that any model must be rebuilt on biotech-specific definitions before it is trusted.

Traditional value quintiles (1 = most expensive)

The drawdown is real and has causes

Since December 2019 the S&P Biotech Index has returned 4.5% a year against 15.1% for the S&P 500, and it is still 21% below its February 2021 peak while the S&P is up 88%. Higher rates choked speculative funding, IRA price-setting cut terminal values, high-profile failures raised the perceived base rate, the 2024 IPO cohort traded ~50% below issue, and, in one banker's words, the generalists are gone. Mean reversion is a tendency, not a schedule.

Annualised return since Dec 2019

Data and execution frictions

13F positions arrive 45 days after quarter-end and 72% of specialist exposure sits in large caps, so the cleanest signal is in the least liquid names. Shorting costs, borrow availability and market impact shrink paper spreads. Every readout is binary, registry dates lag real events, and June / December completion dates are placeholders. SAROS shows the coordinates; it does not resolve the coin flips.

Source for every figure on this page: Verdad Advisers, Biotech Investing: Investment Approaches that Work in a Challenging Industry (Obenshain, Rasmussen & Wintner), drawing on SEC filings and S&P Capital IQ; quintile returns are annualised over Sept 2013 – Oct 2025. Charts are redrawn from the values printed in the paper, not recomputed. Backtests are hypothetical and net of modelled costs; past performance says nothing about the future; none of this is investment advice.

Visuals

the whole snapshot at a glance — all 2026–28 trials, regardless of filters · hover any mark · click a bar, dot or cell to filter the dashboard to it

Therapeutic area × modality

trial counts · top areas × top modalities · click a cell to filter the dashboard to it

Modality: phase mix

share of each modality's trials by phase · count at right · a late-stage-heavy modality is one whose science has already been de-risked

Trials by therapeutic area

stacked by phase · all 2026–28 completions · click to filter

Largest sponsor programs

all registered 2026–28 trials (steel) vs Phase 3 (orange) · the gap is early-stage breadth · click for the program profile

Specialist fund books

13F long book value, latest quarter, log scale · dot area = holdings reported · specialists in bone, generalists in taupe

Longevity companies: capital raised

companies per size bucket · bone = has a registered 2026–28 trial · most of the money sits where there is no registered readout

Phase 3 readouts per quarter by sponsor tier

who owns the pivotal calendar · click a quarter to filter the calendar to it

Trial size by phase

registered enrollment, log scale · bar = middle half (p25–p75), tick = median, whisker = p10–p90
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