Latest / DDReg Knowledge Capsule / The RaaS Revolution in Pharma 2026

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The RaaS Revolution in Pharma 2026 · DDReg Knowledge Capsule

• 0:00
  Speaker 1: Welcome to dj acknowledged capsule. You know, you might think
• 0:03
  Speaker 1: the hardest part of curing a disease is well the science.
• 0:06
  Speaker 2: Yeah, you'd assume it's just the lab work.
• 0:08
  Speaker 1: Right, But right now today there are miracle molecules sitting
• 0:13
  Speaker 1: in labs completely proven to work that you just cannot have.
• 0:17
  Speaker 2: It's actually a bit tragic.
• 0:18
  Speaker 1: Yeah, and why because the sheer volume of paperwork required
• 0:23
  Speaker 1: to get them to you across you know, one hundred
• 0:25
  Speaker 1: and twenty different countries, It's becoming mathematically impossible for humans
• 0:29
  Speaker 1: to keep up.
• 0:30
  Speaker 2: With it, really is. We always imagine the medical finic
• 0:32
  Speaker 2: line is in the laboratory, exactly, but the reality of
• 0:35
  Speaker 2: global medicine is that the real finish line is buried
• 0:40
  Speaker 2: under this massive mountain of ever changing administrative mandates.
• 0:44
  Speaker 1: Which is exactly what we're exploring in today's deep dive.
• 0:46
  Speaker 1: We're looking at a massive operational shift happening right now
• 0:49
  Speaker 1: in twenty twenty six.
• 0:51
  Speaker 2: It's a phenomenal bottleneck, and you are no longer just
• 0:53
  Speaker 2: trying to prove a therapy is safe, right You're trying
• 0:56
  Speaker 2: to prove it one hundred and twenty different ways, in
• 0:58
  Speaker 2: one hundred and twenty different formats to one hundred twenty
• 1:00
  Speaker 2: different regulatory.
• 1:01
  Speaker 1: Bodies, who, by the way, change their minds on a
• 1:03
  Speaker 1: monthly basis.
• 1:04
  Speaker 2: Exactly. So the friction of getting a drug from the
• 1:07
  Speaker 2: lab to the pharmacy is no longer just about the chemistry.
• 1:10
  Speaker 2: It is entirely about navigating this fractured global regulatory landscape.
• 1:16
  Speaker 1: And so the pharmaceutical industry is fundamentally rethinking how it
• 1:20
  Speaker 1: survives this bottleneck. They're ditching the traditional model of these
• 1:24
  Speaker 1: massive permanent internal compliance departments for agile on demand engines.
• 1:29
  Speaker 2: Right, which is what we call regulatory as a service
• 1:31
  Speaker 2: or RHEA.
• 1:32
  Speaker 1: Yeah, right, and using insights and service frameworks from ded
• 1:35
  Speaker 1: reg Pharma, which is a global life science consulting partner,
• 1:39
  Speaker 1: we're going to look under the hood of this transition today.
• 1:41
  Speaker 2: It's a fascinating shift.
• 1:42
  Speaker 1: It is think this deep dive as uncovering the hidden
• 1:45
  Speaker 1: nervous system of global medicine. You know how a new
• 1:48
  Speaker 1: tech strategy is essentially rewiring the system to get therapies
• 1:52
  Speaker 1: into your hands faster.
• 1:53
  Speaker 2: But to really appreciate the scale of this shift, I
• 1:56
  Speaker 2: think we first have to look at the immense weight
• 1:59
  Speaker 2: of what regulatory where as the service is actually replacing.
• 2:01
  Speaker 3: Okay, let's unpack this. What did the old way look like?
• 2:04
  Speaker 2: Well, traditionally a pharmaceutical company had to build all of
• 2:07
  Speaker 2: its regulatory affairs capabilities entirely in house, which is huge massive.
• 2:13
  Speaker 2: That meant hiring literal armies of full time professionals for
• 2:17
  Speaker 2: you know, regulatory strategy and consulting just to plot out
• 2:21
  Speaker 2: the specific legal pathways for a single drug approval.
• 2:25
  Speaker 1: And the strategy is just the tip of the iceberg, right,
• 2:27
  Speaker 1: because then someone actually has to execute the paperwork. Oh Like,
• 2:30
  Speaker 1: if you're listening to this and you work in operations,
• 2:33
  Speaker 1: you know that managing something like an ECTD an electronic
• 2:36
  Speaker 1: common technical document, it isn't just saving a word file
• 2:41
  Speaker 1: as a PDF.
• 2:42
  Speaker 2: Far from it. I mean an ECTD is a highly
• 2:45
  Speaker 2: structured XML backed electronic dossier.
• 2:48
  Speaker 3: It's basically a massive database.
• 2:50
  Speaker 2: Yeah, it links thousands of PDFs, raw clinical data sets,
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  Speaker 2: manufacturing logs. And here's the kicker. If a single hyperlink
• 2:56
  Speaker 2: is broken or a margin is off by a millimeter
• 2:59
  Speaker 2: in a specific regional module a millimeter literally a millimeter,
• 3:03
  Speaker 2: an authority like the FDA or the EMA will hit
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  Speaker 2: you with a refuse defile before they even look at
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  Speaker 2: the science. So you had to have these massive internal
• 3:10
  Speaker 2: teams dedicated purely to submission management and ECDD.
• 3:14
  Speaker 1: Publishing, and then you add an ongoing compliance support right
• 3:17
  Speaker 1: just to monitor the global watchdog exactly.
• 3:20
  Speaker 2: And even after approval, you have product life cycle management right.
• 3:24
  Speaker 1: Okay, wait, let's put a pin in that life cycle
• 3:26
  Speaker 1: management piece because terms like pharmacovigilants or annual product quality
• 3:31
  Speaker 1: reviews apqrs, they get thrown around a lot, sure, but operationally,
• 3:36
  Speaker 1: an APQR isn't just you know, printing a summary report
• 3:39
  Speaker 1: at the end of the year, No.
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  Speaker 2: Not at all. Generating an APQR requires pulling twelve months
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  Speaker 2: of historical batch data, stability test results, supply chain deviations,
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  Speaker 2: patient complaint logs, all to prove what exactly, to mathematically
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  Speaker 2: prove that your manufacturing process remains in a constant state
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  Speaker 2: of control.
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  Speaker 1: And doing that manually, I mean, for dozens of products
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  Speaker 1: across multiple global market it.
• 4:01
  Speaker 2: Takes internal teams weeks if not months, of brute force
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  Speaker 2: data gathering.
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  Speaker 1: Looking at that traditional model, it just sounds completely unsustainable,
• 4:10
  Speaker 1: Like building that internal team is like buying and owning
• 4:14
  Speaker 1: a massive, expensive fleet of specialized vehicles.
• 4:16
  Speaker 2: That's a good way to look at it.
• 4:17
  Speaker 1: Yeah, you purchase snowplows, desert buggies, and Formula one cars,
• 4:22
  Speaker 1: but you only need the snowplow for three weeks out
• 4:25
  Speaker 1: of the year when you're trying to enter one highly
• 4:28
  Speaker 1: specific cold weather market.
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  Speaker 2: Right the rest of.
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  Speaker 1: The time, that multimillion dollar vehicle and it's highly paid
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  Speaker 1: specialized driver, they're just sitting in your corporate garage gathering dust.
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  Speaker 2: And the fixed overhead costs of that fleet, the salaries,
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  Speaker 2: the specialized enterprise software licenses, that continuous training to keep
• 4:45
  Speaker 2: everyone current on global laws. It's just astronomical.
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  Speaker 3: So how does rest fix that?
• 4:51
  Speaker 2: Well. Regulatory as a Service introduces an entirely agile operational model.
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  Speaker 2: It allows pharma firms to essentially rent regulatory expertise and
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  Speaker 2: tech enabled workflows strictly on demand.
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  Speaker 1: So it is basically a premium enterprise level ride sharing
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  Speaker 1: service for NICHE compliance. If a company needs to get
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  Speaker 1: a new oncology drug approved in Japan, they just summon
• 5:12
  Speaker 1: the exact specialized vehicle and driver they need for the
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  Speaker 1: PMDA market right when they.
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  Speaker 2: Need it, spot on, and crucially, they don't pay for
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  Speaker 2: it when they're operating in regions that don't require that
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  Speaker 2: specific expertise.
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  Speaker 3: Right, that makes total sense.
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  Speaker 2: Providers like d D reg act as seamless extensions of
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  Speaker 2: the client's internal teams. They offer end to end support
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  Speaker 2: starting from the initial gap analysis of the clinical data
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  Speaker 2: all the way through global market authorizations and the post
• 5:40
  Speaker 2: marketing compliance we just discussed.
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  Speaker 3: So it slashes the fixed.
• 5:43
  Speaker 2: Overhead, oh yeah. But more importantly, it accelerates the actual
• 5:47
  Speaker 2: approval timelines because you're accessing specialized expertise instantly.
• 5:51
  Speaker 1: Okay, But if that specialized vehicle fleet has always been
• 5:54
  Speaker 1: wildly expensive to maintain, what is forcing this massive tipping
• 5:58
  Speaker 1: point toward ROS now twenty twenty six.
• 6:01
  Speaker 2: That's the big question, right.
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  Speaker 1: Because we all know the pressure to cut overhead has
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  Speaker 1: always existed in the corporate world. If this were purely
• 6:07
  Speaker 1: a balance sheet decision, they would have made this pivot
• 6:09
  Speaker 1: a decade ago, right.
• 6:11
  Speaker 2: But the catalyst isn't the balance sheet, it's regulatory velocity.
• 6:15
  Speaker 3: Regulatory velocity.
• 6:16
  Speaker 2: Yeah, we've hit a point where the sheer volume of
• 6:20
  Speaker 2: global framework updates makes it mathematically impossible for any localized
• 6:24
  Speaker 2: human team to keep up. Global health authorities are overhauling
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  Speaker 2: their requirements at a pace we have never.
• 6:30
  Speaker 1: Seen before and demanding digital integration too.
• 6:33
  Speaker 2: Exactly real time digital integration.
• 6:35
  Speaker 1: Let's ground this for the listener, though. What is happening
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  Speaker 1: right now out in the world that is fundamentally breaking
• 6:40
  Speaker 1: the old in house system?
• 6:42
  Speaker 2: Okay, well, we can start with the EU regulatory reforms. Okay,
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  Speaker 2: the European Medicines Agency has instituted incredibly strict digital submission standards.
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  Speaker 2: They aren't just asking for PDFs anymore.
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  Speaker 3: What do they want?
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  Speaker 2: They're requiring continuous dynamic pipeline adjustments just to interface with
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  Speaker 2: their central submission systems. Your IT architecture has to be
• 7:03
  Speaker 2: constantly updated to match their portal requirements.
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  Speaker 3: That sounds like a nightmare for an IT department.
• 7:08
  Speaker 2: It is, But an even more striking example of this
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  Speaker 2: fragmentation is happening right now in India.
• 7:13
  Speaker 1: With the CDSO, right, the Central Drug Standard Control Organization.
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  Speaker 2: Yes, with the launch of the Indian Pharmacopia twenty twenty
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  Speaker 2: six standards, the CdSeO introduced highly specific, entirely novel metrics
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  Speaker 2: for blood and blood components.
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  Speaker 1: And are those metrics used anywhere else?
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  Speaker 2: Nope, there are no comparable metrics or testing standards for
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  Speaker 2: these specific biological markers. Anywhere else in the world.
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  Speaker 1: Let's just think about the operational nightmare that creates. Like
• 7:41
  Speaker 1: a global pharma company with the centralized team in New
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  Speaker 1: Jersey or Basel, has a standardized way of measuring and
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  Speaker 1: reporting on blood components, right, and that standard satisfies the FDA,
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  Speaker 1: the EMA, and like ninety percent of their other markets.
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  Speaker 1: But suddenly to sell in India, the lab has to
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  Speaker 1: recalibrate its equipment, separate that data stream, and generally an
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  Speaker 1: entirely bespoke compliance report just for the twenty twenty six standards.
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  Speaker 2: Yes, and the internal regulatory team has to halt their workflow,
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  Speaker 2: learn this hyper local framework, implement it into the ECTD,
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  Speaker 2: and somehow ensure that this new reporting standard doesn't inadvertently
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  Speaker 2: contradict the data they are simultaneously filing in Europe or Japan.
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  Speaker 1: So it fractures the central database.
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  Speaker 2: Completely fractures it. And this complexity extends beyond clinical metrics too.
• 8:27
  Speaker 3: What else is there?
• 8:28
  Speaker 2: Well, we're seeing a massive expansion in environmental, social and
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  Speaker 2: governance ESG tracking requirements baked directly into pharmaceutical supply chain audits.
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  Speaker 2: Oh wow, yeah, intertwined with hyper strict global data privacy laws.
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  Speaker 2: Authorities now expect real time compliance monitoring on where materials
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  Speaker 2: are sourced and how patient data is siloed.
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  Speaker 1: Trying to run a global launch like that is like
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  Speaker 1: playing one hundred and twenty different games of chess simultaneously, exactly,
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  Speaker 1: except you know the rule for how the night moves
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  Speaker 1: changes every five minutes depending on which board you were
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  Speaker 1: looking at.
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  Speaker 2: That is exactly what it feels like.
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  Speaker 1: So the specialized knowledge aspect of race isn't just about
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  Speaker 1: saving money on consultants. It is a matter of basic survival.
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  Speaker 1: A central in house team simply cannot play one hundred
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  Speaker 1: and twenty different games of chess.
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  Speaker 2: At once, which brings us to the operational paradox.
• 9:15
  Speaker 3: Okay, what's the paradox?
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  Speaker 2: If an in house team of five hundred people cannot
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  Speaker 2: keep up with this global fragmentation, throwing more humans at
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  Speaker 2: the problem doesn't solve it for the race's providers either.
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  Speaker 1: Oh right, Because if dd reg is managing this for
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  Speaker 1: dozens of different enterprise clients across one hundred and twenty countries,
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  Speaker 1: they can't achieve it just by hiring one thousand more
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  Speaker 1: consultants exactly.
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  Speaker 2: You'd just be shifting the human bottleneck from the pharma
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  Speaker 2: company to the vendor.
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  Speaker 3: So how do they do it?
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  Speaker 1: What is the actual mechanism that prevents the RAYS provider
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  Speaker 1: from being crushed by the exact same regulatory weight.
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  Speaker 2: The engine driving the RAYS revolution in twenty twenty six
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  Speaker 2: is a fundamental integration of autonomous AI agents and customized
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  Speaker 2: machine learning regulatory software.
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  Speaker 3: Of course it is.
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  Speaker 2: Yeah, the core capability relies on advanced natural language processing
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  Speaker 2: and supervised AI.
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  Speaker 1: Okay, walk me through the mechanics of that. How does
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  Speaker 1: an AI agent take raw lab data and turn it
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  Speaker 1: into something a government inspector actually signs off on?
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  Speaker 2: So these semi autonomous agents plug directly into a client's
• 10:17
  Speaker 2: unstructured RD databases. They act as a hyper advanced translation engine.
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  Speaker 3: Translation engine.
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  Speaker 2: Yeah, but it's not just translating words from English to Japanese.
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  Speaker 2: It is taking the raw science dialect of the research
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  Speaker 2: team and simultaneously mapping it into the hyper specific legal
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  Speaker 2: dialects of one hundred and twenty different global jurisdictions.
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  Speaker 3: That's wild.
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  Speaker 2: The AI cross references the clinical data against real time
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  Speaker 2: updates from local authorities, instantly flagging compliance risks like the
• 10:45
  Speaker 2: new Indian blood metrics before a human even touches the file.
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  Speaker 1: Okay, so it functions like a universal translator at the
• 10:52
  Speaker 1: United Nations, but for molecular biology and international trade law.
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  Speaker 2: That is a brilliant way to conceptualize it. And it
• 11:00
  Speaker 2: scales up to what the industry calls in silico dossier.
• 11:03
  Speaker 1: Generation, meaning entirely computer simulated and computer generated applications.
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  Speaker 2: Right. The AI graps and structure is the regulatory submissions electronically.
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  Speaker 2: Because it understands the semantic mapping of the XML structures
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  Speaker 2: required for an ECTD, it drastically minimizes the marginal effort needed.
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  Speaker 1: Per market, so you aren't starting from scratch every time exactly.
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  Speaker 2: Instead of a human rewriting a dossia fifty times for
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  Speaker 2: fifty countries, the AI adapts the core clinical data into
• 11:29
  Speaker 2: fifty perfectly compliant localized formats. Simultaneously, it builds the XML backbone,
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  Speaker 2: hyperlinks the data sets, and formats the margins to the millimeter.
• 11:39
  Speaker 1: Okay, I need to pause here, sure, because if you
• 11:41
  Speaker 1: are an operations executive listening to this, alarms are probably.
• 11:44
  Speaker 3: Going off in your head right now.
• 11:45
  Speaker 2: Oh, I'm sure they are.
• 11:47
  Speaker 1: We are talking about granting autonomous AI agents direct access
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  Speaker 1: to highly confidential R INDEED data the.
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  Speaker 2: Literal blueprints to multi billion dollar intellectual.
• 11:57
  Speaker 1: Property exactly, and we are letting it draft drug approval
• 12:00
  Speaker 1: documents for the FDA. How on earth does a RAY
• 12:04
  Speaker 1: ask provider guarantee GDPR compliance, prevent data leakage into public
• 12:08
  Speaker 1: AI models, and ensure the AI doesn't hallucinate a critical
• 12:13
  Speaker 1: scientific metric.
• 12:14
  Speaker 2: It's the most common question, and the security and validation
• 12:17
  Speaker 2: frameworks are honestly the most critical components of modern RAS infrastructure.
• 12:21
  Speaker 2: I would hope so providers do not use public large
• 12:24
  Speaker 2: language models or open web servers. These platforms operate within
• 12:28
  Speaker 2: highly secure, single tenant cloud environments with zero trust architecture
• 12:33
  Speaker 2: and advanced data encryption.
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  Speaker 3: So it's totally isolated.
• 12:36
  Speaker 2: Yes, the R and D information is completely siloed. The
• 12:39
  Speaker 2: AI model trains strictly on the client's internal data and
• 12:42
  Speaker 2: the public regulatory laws, never sharing that intellectual property outward.
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  Speaker 1: It is a totally close ecosystem. The AI isn't learning
• 12:50
  Speaker 1: from Company A's cancer drug to help Company BE write
• 12:54
  Speaker 1: a better dossier.
• 12:55
  Speaker 2: Never. The partitioning is absolute, just to comply with GDPR
• 12:59
  Speaker 2: and global IP law.
• 13:00
  Speaker 1: Okay, but what about the hallucination risks?
• 13:02
  Speaker 2: Addressing your second concern, the risk of AI hallucinating or
• 13:06
  Speaker 2: misinterpreting the science is where global authorities have drawn a
• 13:09
  Speaker 2: very hard line.
• 13:10
  Speaker 3: Oh, the regulator stepped in heavily.
• 13:12
  Speaker 2: The FDA, the EMA, and others mandate a strict human
• 13:15
  Speaker 2: in the loop framework. The pharmaceutical sponsor remains one hundred
• 13:18
  Speaker 2: percent accountable for the submission. AI cannot act entirely alone.
• 13:22
  Speaker 1: Okay, but I have to challenge the efficiency of that
• 13:24
  Speaker 1: human in the loop model.
• 13:25
  Speaker 2: Go for it.
• 13:26
  Speaker 1: If the AI is generating fifty localized dossiers simultaneously to
• 13:29
  Speaker 1: save time, but a human expert still has to manually
• 13:33
  Speaker 1: read thousands of pages across all fifty dossiers before hitting send.
• 13:37
  Speaker 1: Hasn't the human validation process just become the new bottleneck?
• 13:40
  Speaker 1: How does that actually scale?
• 13:42
  Speaker 2: That's a fair point, But it scales because the nature
• 13:45
  Speaker 2: of the human validation changes entirely. How so the experts
• 13:48
  Speaker 2: aren't reading fifty dossiers from scratch. The RAS platforms utilize
• 13:52
  Speaker 2: sophisticated confidence scoring. Confidence scoring, Yeah, When the AI generates
• 13:56
  Speaker 2: the localized documents, it flags every single data mapping with
• 14:00
  Speaker 2: a confidence metric. If it maps the standard stability test,
• 14:03
  Speaker 2: the confidence is ninety nine point nine.
• 14:05
  Speaker 1: Percent because it's seen it a million times exactly.
• 14:08
  Speaker 2: But if it encounters a novel interpretation of say India's
• 14:11
  Speaker 2: new Blood metric, it flags that specific paragraph with a
• 14:14
  Speaker 2: low confidence score, directing the human expert exactly where their
• 14:18
  Speaker 2: critical thinking is required.
• 14:19
  Speaker 1: Oh wow, So the AI is essentially highlighting its own
• 14:22
  Speaker 1: work and saying, I am certain about these nine thousand pages,
• 14:25
  Speaker 1: but you need to check my logic on this one
• 14:27
  Speaker 1: specific paragraph.
• 14:29
  Speaker 2: You nailed it. It allows the human experts, whether they're
• 14:32
  Speaker 2: internal to the pharma company or the vendors' specialists, to
• 14:36
  Speaker 2: perform highly targeted validation that changes everything it does. They
• 14:41
  Speaker 2: verify the complex scientific strategy and the nuanced regulatory translations
• 14:46
  Speaker 2: while trusting the AI to handle the brute force formatting
• 14:50
  Speaker 2: and cross referencing. AI is the engine, but the human
• 14:54
  Speaker 2: is steering and applying the brakes.
• 14:56
  Speaker 1: This massive leap in efficiency and accuracy brings us to
• 14:59
  Speaker 1: the financial res reality of twenty twenty six because if
• 15:02
  Speaker 1: the RAS provider is wielding this incredibly powerful AI engine,
• 15:06
  Speaker 1: it has to completely upend the traditional business models of
• 15:10
  Speaker 1: pharmaceutical software.
• 15:11
  Speaker 2: Right. Oh, absolutely, we all know.
• 15:12
  Speaker 1: The trap of the standard sauce model software as a service.
• 15:16
  Speaker 3: You pay a.
• 15:16
  Speaker 1: Massive monthly licensing fee for a platform, and whether that
• 15:20
  Speaker 1: tool actually solves your compliance problem or not, well, the
• 15:22
  Speaker 1: vendor still gets paid Exactly the.
• 15:24
  Speaker 2: Standard sauce model pushes all the operational risk onto the
• 15:27
  Speaker 2: pharmaceutical company. If your internal team makes a mistake while
• 15:30
  Speaker 2: using a vendor software and your drug launch is delayed
• 15:33
  Speaker 2: by six months, the vendor isn't penalized.
• 15:37
  Speaker 1: They still collect their monthly check yep.
• 15:40
  Speaker 2: But Ratus fundamentally rewires this dynamic by moving to risk
• 15:45
  Speaker 2: sharing outcome based pricing models.
• 15:48
  Speaker 1: Wait, wait, you were telling me a vendor is willing
• 15:50
  Speaker 1: to absorb the financial risk of a delayed multi million
• 15:54
  Speaker 1: dollar drug launch. Yes, vendors are charging per dossier, per
• 15:58
  Speaker 1: approval or by milestone.
• 16:01
  Speaker 2: That's the new standard.
• 16:02
  Speaker 1: How is that a sustainable business model?
• 16:04
  Speaker 3: For arras a provider?
• 16:06
  Speaker 1: If their AI misses a formatting rule and a dossier
• 16:09
  Speaker 1: is rejected, they just eat the cost.
• 16:11
  Speaker 2: They assume the associated operational costs to correct and resubmit. Yes,
• 16:14
  Speaker 2: they are essentially guaranteeing the outcome of being audit ready.
• 16:18
  Speaker 1: That's a bold guarantee, it is.
• 16:20
  Speaker 2: But it is a sustainable business model for them for
• 16:22
  Speaker 2: one very specific reason, which is proactive auditing.
• 16:25
  Speaker 1: Okay, what does that mean?
• 16:26
  Speaker 2: The RAYS networks employ their AI to run continuous mock
• 16:30
  Speaker 2: digital inspections on the company's data repositories, so.
• 16:33
  Speaker 1: They are auditing themselves before the government ever gets the.
• 16:36
  Speaker 2: Chance continuously, just like an insurance actuary using a supercomputer.
• 16:40
  Speaker 2: The RAYS provider only accepts the financial risk of the
• 16:43
  Speaker 2: outcome because their AI has already stress tested the data
• 16:47
  Speaker 2: against the latest rules from the FDA, EMA and CDSKEO.
• 16:51
  Speaker 3: So they already know it's going to pass.
• 16:53
  Speaker 2: Mostly. Yes, they shift the entire paradigm of the pharmaceutical
• 16:56
  Speaker 2: company from reactive compliance, you know, scrambling to gather documents
• 17:01
  Speaker 2: when an inspector shows up to a permanent, always audit
• 17:04
  Speaker 2: ready status.
• 17:05
  Speaker 3: That's incredible.
• 17:06
  Speaker 1: If a regulatory body asks a question, the answer has
• 17:09
  Speaker 1: already been verified by the AI and is waiting in.
• 17:12
  Speaker 3: The repository exactly, So.
• 17:13
  Speaker 1: The business leader isn't just paying for a software tool,
• 17:16
  Speaker 1: They are purchasing the mathematical certainty of compliance.
• 17:19
  Speaker 2: And that certainty is what allows pharmaceutical companies to adapt
• 17:22
  Speaker 2: to rapid global shifts seamlessly. When the EU introduces new
• 17:26
  Speaker 2: digital portals, or India enforces highly specific twenty twenty six
• 17:30
  Speaker 2: blood metrics. The ray Ass model absorbs that friction entirely.
• 17:34
  Speaker 1: Meaning the core scientific mission of the company isn't derailed
• 17:37
  Speaker 1: by bureaucratic updates exactly.
• 17:39
  Speaker 2: The scientists get to focus on science.
• 17:41
  Speaker 1: So let's bring this all together for you listening right now.
• 17:44
  Speaker 1: We started by looking at the staggering operational bottleneck of
• 17:48
  Speaker 1: getting a drug approved across one hundred and twenty different countries.
• 17:51
  Speaker 2: It's quite the maze, it really is, and.
• 17:54
  Speaker 1: Ross Pharma is proving that it is no longer just
• 17:56
  Speaker 1: about outsourcing your paperwork to a consultancy. It evolved into
• 18:00
  Speaker 1: an essential technological strategy. By combining autonomous AI agents with
• 18:05
  Speaker 1: risk sharing outcome based pricing, companies can achieve a permanent
• 18:10
  Speaker 1: state of audit readiness.
• 18:12
  Speaker 2: So what here is the real world impact streamlining this
• 18:16
  Speaker 2: massive bureaucratic bottleneck through advanced platforms like dregs of Italic
• 18:22
  Speaker 2: LC for comprehensive life cycle tracking or their Reginel platform
• 18:26
  Speaker 2: for real time global intelligence. It means that the timeline
• 18:30
  Speaker 2: from a successful clinical trial to a patient actually receiving
• 18:33
  Speaker 2: the medication is drastically compressed.
• 18:35
  Speaker 1: The friction is just removed from the system. Life saving
• 18:38
  Speaker 1: therapy is cross borders faster and safer than ever.
• 18:40
  Speaker 2: Before, which is the ultimate goal right.
• 18:42
  Speaker 1: Which leaves us with a final somewhat provocative thought to ponder.
• 18:45
  Speaker 1: Let's hear it if regulatory as a service in AI
• 18:49
  Speaker 1: continue this trajectory and the friction of regulatory approval drops
• 18:53
  Speaker 1: to near zero. I mean, if managing the bureaucracy becomes
• 18:56
  Speaker 1: an automated, perfectly executed background process, the biggest hurdle to
• 19:01
  Speaker 1: global medicine will shift away from government red tape entirely.
• 19:04
  Speaker 2: It completely removes the administrative shield exactly.
• 19:08
  Speaker 1: It shines a glaring, unavoidable spotlight purely on the speed
• 19:11
  Speaker 1: and efficacy of the underlying science. We might finally get
• 19:15
  Speaker 1: to a point where a pharmaceutical company can no longer
• 19:17
  Speaker 1: blame a delayed launch on a complex regulatory filing in
• 19:21
  Speaker 1: India or Europe.
• 19:22
  Speaker 2: The only thing standing between a laboratory discovery and a
• 19:25
  Speaker 2: patient's cure will be the biology.
• 19:27
  Speaker 3: Itself, which is how it should be.
• 19:28
  Speaker 1: It is a profound shift and accountability, and it is
• 19:31
  Speaker 1: the future. These platforms are building right now. Well said
• 19:34
  Speaker 1: something to keep in mind The next time you hear
• 19:36
  Speaker 1: about a medical breakthrough. Until next time, keep diving deep.