drug safety Articles / Blogs / Perficient

Agentic AI for Real‑Time Pharmacovigilance on Databricks

David Callaghan — Wed, 01 Oct 2025 18:12:02 +0000

Adverse drug reaction (ADR) detection is a primary regulatory and patient-safety priority for life sciences and health systems. Traditional pharmacovigilance methods often depend on delayed signal detection from siloed data sources and require extensive manual evidence collection. This legacy approach is time-consuming, increases the risk of patient harm, and creates significant regulatory friction. For solution architects and engineers in healthcare and finance, optimizing data infrastructure to meet these challenges is a critical objective and a real headache.

Combining the Databricks Lakehouse Platform with Agentic AI presents a transformative path forward. This approach enables a closed-loop pharmacovigilance system that detects high-quality safety signals in near-real time, autonomously collects corroborating evidence, and routes validated alerts to clinicians and safety teams with complete auditability. By unifying data and AI on a single platform through Unity Catalog, organizations can reduce time-to-signal, increase signal precision, and provide the comprehensive data lineage that regulators demand. This integrated model offers a clear advantage over fragmented data warehouses or generic cloud stacks.

The Challenges in Modern Pharmacovigilance

To build an effective pharmacovigilance system, engineers must integrate a wide variety of data types. This includes structured electronic health records (EHR) in formats like FHIR, unstructured clinical notes, insurance claims, device telemetry from wearables, lab results, genomics, and patient-reported outcomes. This process presents several technical hurdles:

Data Heterogeneity and Velocity: The system must handle high-velocity streams from devices and patient apps alongside periodic updates from claims and EHR systems. Managing these disparate data types and speeds without creating bottlenecks is a significant challenge.
Sparse and Noisy Signals: ADR mentions can be buried in unstructured notes, timestamps may conflict across sources, and confounding variables like comorbidities or polypharmacy can obscure true signals.
Manual Evidence Collection: When a potential signal is flagged, safety teams often must manually re-query various systems and request patient charts, a process that delays signal confirmation and response.
Regulatory Traceability: Every step, from detection to escalation, must be reproducible. This requires clear, auditable provenance for both the data and the models used in the analysis.

The Databricks and Agentic AI Workflow

An agentic AI framework running on the Databricks Lakehouse provides a structured, scalable solution to these problems. This system uses modular, autonomous agents that work together to implement a continuous pharmacovigilance workflow. Each agent has a specific function, from ingesting data to escalating validated signals.

Step 1: Ingest and Normalize Data

The foundation of the workflow is a unified data layer built on Delta Lake. Ingestion & Normalization Agents are responsible for continuously pulling data from various sources into the Lakehouse.

Continuous Ingestion: Using Lakeflow Declarative Pipelines and Spark Structured Streaming, these agents ingest real-time data from EHRs (FHIR), claims, device telemetry, and patient reports. Data can be streamed from sources like Kafka or Azure Event Hubs directly into Delta tables.
Data Normalization: As data is ingested, agents perform crucial normalization tasks. This includes mapping medical codes to standards like RxNorm, SNOMED, and LOINC. They also resolve patient identities across different datasets using both deterministic and probabilistic linking methods, creating a canonical event timeline for each patient. This unified view is essential for accurate signal detection.

Step 2: Detect Signals with Multimodal AI

Once the data is clean and unified, Signal Detection Agents apply a suite of advanced models to identify potential ADRs. This multimodal approach significantly improves precision.

Multimodal Detectors: The system runs several types of detectors in parallel. Clinical Large Language Models (LLMs) and fine-tuned transformers extract relevant entities and context from unstructured clinical notes. Time-series anomaly detectors monitor device telemetry for unusual patterns, such as spikes in heart rate from a wearable.
Causal Inference: To distinguish true causality from mere correlation, statistical and counterfactual causal engines analyze the data to assess the strength of the association between a drug and a potential adverse event.
Scoring and Provenance: Each potential ADR is scored with an uncertainty estimate. Crucially, the system also attaches provenance pointers that link the signal back to the specific data and model version used for detection, ensuring full traceability.

Step 3: Collect Evidence Autonomously

When a candidate signal crosses a predefined confidence threshold, an Evidence Collection Agent is activated. This agent automates what is typically a manual and time-consuming process.

Automated Assembly: The agent automatically assembles a complete evidence package. It extracts relevant sections from patient charts, re-runs queries for lab trends, fetches associated genomics variants, and pulls specific windows of device telemetry data.
Targeted Data Pulls: If the initial evidence is incomplete, the agent can plan and execute targeted data pulls. For example, it could order a specific lab test, request a clinician chart review through an integrated system, or trigger a patient survey via a connected app to gather more information on symptoms and dosing adherence.

Step 4: Triage and Escalate Signals

With the evidence gathered, a Triage & Escalation Agent takes over. This agent applies business logic and risk models to determine the appropriate next step.

Composite Scoring: The agent aggregates all collected evidence and computes a composite risk and confidence score for the signal. It applies configurable business rules based on factors like event severity and regulatory reporting timelines.
Intelligent Escalation: For high-risk or ambiguous signals, the agent automatically escalates the issue to human safety teams by creating tickets in systems like Jira or ServiceNow. For clear, high-confidence signals that pose a lower operational risk, the system can be configured to auto-generate regulatory reports, such as 15-day expedited submissions, where permitted.

Step 5: Enable Continuous Learning

The final agent in the workflow closes the loop, ensuring the system improves over time. The Continuous Learning Agent uses feedback from human experts to refine the AI models.

Feedback Integration: Outcomes from chart reviews, follow-up labs, and final regulatory adjudications are fed back into the system’s training pipelines.
Model Retraining and Versioning: This new data is used to retrain and refine the signal detectors and causal models. MLflow tracks these updates, versioning the new models and linking them to the training data snapshot. This creates a fully auditable and continuously improving system that meets strict regulatory standards for model governance.

The Technical Architecture on Databricks

The power of this workflow comes from the tightly integrated components of the Databricks Lakehouse Platform.

Data Layer: Delta Lake serves as the single source of truth, storing versioned tables for all data types. Unity Catalog manages fine-grained access policies, including row-level masking, to protect sensitive patient information.
Continuous ETL & Feature Store: Delta Live Tables provide schema-aware pipelines for all data engineering tasks, while the integrated Feature Store offers managed feature views for models, ensuring consistency between training and inference.
Detection & Inference: Databricks provides integrated GPU clusters for training and fine-tuning clinical LLMs and other complex models. MLflow tracks experiments, registers model versions, and manages deployment metadata.
Agent Orchestration: Lakeflow Jobs coordinate the execution of all agent tasks, handling scheduling, retries, and dependencies. The agents themselves can be lightweight microservices or notebooks that interact with Databricks APIs.
Serving & Integrations: The platform offers low-latency model serving endpoints for real-time scoring. It can integrate with clinician portals via SMART-on-FHIR, ticketing systems, and messaging services to facilitate human-in-the-loop workflows.

Why This Approach Outperforms Alternatives

Architectures centered on traditional data warehouses like Snowflake often struggle with this use case because they separate storage from heavy ML compute. Tasks like LLM inference and streaming feature engineering require external GPU clusters and complex orchestration, which introduces latency, increases operational overhead, and fractures data lineage across systems. Similarly, a generic cloud stack requires significant integration effort to achieve the same level of data and model governance.

The Databricks Lakehouse co-locates multimodal data, continuous pipelines, GPU-enabled model lifecycles, and governed orchestration on a single, unified platform. This integration dramatically reduces friction and provides a practical, auditable, and scalable path to real-time pharmacovigilance. For solution architects and engineers, this means a faster, more reliable way to unlock real-time insights from complex healthcare data, ultimately improving patient safety and ensuring regulatory compliance.

Conclusion

By harnessing Databricks’ unified Lakehouse architecture and agentic AI, organizations can transform pharmacovigilance from a reactive, manual process into a proactive, intelligent system. This workflow not only accelerates adverse drug reaction detection but also streamlines evidence collection and triage, empowering teams to respond swiftly and accurately. The platform’s end-to-end traceability, scalable automation, and robust data governance support stringent regulatory demands while driving operational efficiency. Ultimately, implementing this modern approach leads to better patient outcomes, reduced risk, and a future-ready foundation for safety monitoring in life sciences.

Perficient is a Databricks Elite Partner. Contact us to learn more about how to empower your teams with the right tools, processes, and training to unlock your data’s full potential across your enterprise.

5 Takeaways From Our “Improve Medical Product Information Sharing With Virtual Agents” Webinar

Madeline McDermott — Mon, 17 Jan 2022 17:39:59 +0000

Our life sciences and technology experts recently delivered the webinar, “Improve Medical Product Information Sharing With Virtual Agents,” where they discussed how automation and artificial intelligence can be used to optimize call center operations and improve end-user experiences.

Here are five key takeaways:

Just because a system is powered by AI doesn’t mean you have to sacrifice empathy. Systems can be designed to have a natural conversation flow and recognize whether a message is negative or positive. For example, suppose someone calls to inquire whether they should give their puppy more medicine because it vomited shortly after taking its dose. In that case, an AI system can be programmed to compassionately respond with, “I’m sorry to hear that,” before searching its database for the accurate medical advice to relay.
AI isn’t meant to replace the call agent, but rather, its purpose is to allow them to focus on higher-value escalations. The severity of adverse reactions and urgent HCP questions can vary significantly from case to case. Conversations with live agents can be prioritized and triaged to quickly route those calls to the best call center resource.
AI can help address specific call center challenges. Many pharmaceutical and medical call centers experience extremely high call volumes, especially at certain times of the year (i.e., flu season), resulting in unacceptably long wait times and excessive dropped calls. Call center agents are also challenged with having to meticulously record their interactions, which only exacerbates these issues. AI can use NLP to help address these issues and record interactions. The great thing is that it interfaces with current systems, works in any regulatory area (e.g., biologic, device, animal health, human health, dietary supplements), and can be deployed globally to overcome language barriers.
AI virtual agents can be fine-tuned to effectively handle various types of callers. For example, a virtual agent that speaks with doctors may be programmed to communicate using more medical vocabulary than a virtual agent designed to speak with patients.
An AI virtual agent delivered in a truly omnichannel capacity will greatly reduce frictions in the user experience. Suppose someone is experiencing an adverse reaction to a medication that gives them a sore throat. In that case, a texting method of communication may be better suited for them than a phone call, and AI systems can equip users with such options. If someone is at the point of sale and has questions about an OTC product or their prescription, they could easily text with questions or concerns.

Curious to learn more? Watch the recording here or below.

Industry Slant // Kari Blaho-Owens on Montana, Aviation, and Pharmacovigilance

Madeline McDermott — Fri, 07 Jan 2022 14:40:44 +0000

Kari Blaho-Owens, Ph.D., is Perficient’s Director of Pharmacovigilance, Safety, and Regulatory Affairs. She leads a team that provides PV, regulatory, risk management knowledge, and consulting to pharma and CROs. Perficient also hosts PV-related applications, configure, validate and maintain PV adverse event databases, and reporting solutions. At the end of the day, we contribute to patient safety by providing the means to ensure that drugs are safe and effective. Kari has more than 25 years of experience building and supporting global safety and regulatory initiatives for pharmaceutical, medical device, animal health, and clinical research organizations (CROs).

Kari Blaho-Owens joins Madeline McDermott and Eugene Sefanov for a Microsoft Teams Chat

“Huntin’, Fishin’, and Lovin’ Every Day”

Madeline McDermott: First things first. Where were you born?

Kari Owens: I was born in Coral Gables, Florida.

MM: Did you spend most of your childhood there?

KO: My family moved pretty often when I was little. I lived in Mississippi and Texas, and when I was about 10 or 11, we settled in a small, rural town in Arkansas. There wasn’t even a McDonald’s nearby until I was in high school. That’s where I grew up and consider home.

MM: Where do you live currently?

Kari taking a photo in Sunday Falls, in Stryker, Montana

KO: Eureka, Montana. It’s such a beautiful mix of people, land, culture. It’s awesome!

MM: What’s the population of Eureka?

KO: There are around 1,300 people – but it’s not as rural as you’d think. We’re just very spread out.

MM: Where did you live before Montana?

KO: Before moving to Montana, I lived in Bennett, North Carolina. North Carolina really morphed in a short period of time because a lot of technology and pharma moved there.

MM: Why did you end up moving away from North Carolina?

KO: We were looking for a place that was different. I wanted to live on a river where I could fly fish, hunt, and take pictures of the amazing scenery. We were fortunate to find a place on the Tobacco River. There is a lot of history here, and the people are lovely. And it wouldn’t be possible to live here if it weren’t for my role at Perficient. The company and role allow me to work anywhere.

Kari catches a little red trout

Kari when she brought home her golden retriever puppy, Trip

MM: You must really love nature.

KO: I think that’s the thing that makes living here so awesome; you can look out at any time of the day and see all this wildlife.

We had a group of deer that came through last week. I was on my porch giving out some dry corn to the birds when I saw them. I held out my hand super still, and a doe came up and ate some of the corn out of my hand. And then she put her head on my shoulder. It was just amazing.

***

From White-Knuckle Flying to Volunteering

MM: I see that the sign behind you says, “Shelby Aviation.” Tell me about that.

KO: When I was in academia and traveling quite a bit, I was a white-knuckle flier. Let’s just say physics and math are unpleasant for me. To confront this, I thought I’d go to ground school to get a better understanding of the physics and math behind flying and how a 250,000-pound metal tube stays in the air. I thought it would make me more comfortable.

I then thought I’d buy three hours of airtime with an instructor to see if I couldn’t “kiss the dragon.” I spent the first 45 minutes sitting on my hands. My instructor finally had me take the yolk for a bit.

Something happens while flying…it’s like when you’re in a boat and you hit a backwash. You can just feel it. Once you’ve done that in the air, it’s like a sickness. There was no stopping after that.

I started flying with these guys at Shelby Aviation in Millington, Tennessee, where I had a Navy instructor who taught me more, let’s just say, new vocabulary, than I had ever heard in my life. He was an extraordinary pilot.

Kari and her air instructor at the world’s largest airshow and in front of a P51 Mustang airplane

I went on to get my private, instrument rating, then my multi-engine commercial industry rating. Next, I would like to earn my seaplane rating because there are lots of lakes in the mountains here. I’d also like to try flying a helicopter.

It’s never been just about flying for the — what they used to call the “$100 hamburger.” By the way, it’s more like the “$400 hamburger” now, when you consider inflation.

I got involved volunteering with Veterans Airlift Command, an organization that provides free air transportation to those wounded in combat, as well as their families, for medical care. I also flew with Angel Flight, an organization that flies patients to points of care for medical treatment. There was also a third group that I helped support, too, that was formed right after 9/11, and its mission was to recruit and train general aviation pilots to fly supplies or whatever else was needed in case we encountered that type of crisis again.

MM: Did you do a lot of those types of flights over the years?

KO: I did as much as time allowed. While I lived in Atlanta, we flew veterans with disabilities to Shepherd Center, a patient rehabilitation hospital for the military wounded.

When we lived in Tennessee, we flew a lot of kids to St. Jude Children’s Research Hospital.

During Hurricane Katrina, we flew a lot of supplies down from Memphis as far down south as we could to get them to the National Guard.

It was a real blessing to be able to do this. These groups opened a lot of opportunities, and through them, I have met so many incredible people.

There is a lot you can do with general aviation, and I’d encourage anyone who dreams of flying to try it. Like many things in life, it may not be what you think it is, but it has been an extraordinary privilege and blessing.

***

“No Three-Year-Old Wakes Up and Thinks ‘I want to work in pharmacovigilance.’”

MM: What was your first job?

KO: My first job or my worst job?

MM: Both!

KO: My first job was nannying and housekeeping for a family in my hometown in Arkansas. The shortest job I ever had was a waitress – it’s one of the most difficult jobs in the world – I lasted four days.

MM: What was your first corporate job?

KO: My first corporate job was with Schering-Plough in the consumer and OTC health division. Right after they approved Claritin to be sold over the counter, the company needed a pharmacovigilance group that could integrate with its medical information and global PV group. I was hired to build a team that could support Claritin and manage the legacy products in the rest of the Schering-Plough line. The company had everything from wart removers to laxatives. You can imagine the number of cases we got.

MM: How did you end up getting into the pharmacovigilance space?

KO: No three-year-old wakes up and thinks, “I think I want to work in pharmacovigilance.” I worked in the inner-city emergency department at the Elvis Presley Memorial Trauma Center as the research director in the ER. It’s a level 1 trauma center that takes patients from a four-state area. We had a research program, and that’s when I got involved working on clinical studies around toxicology, envenomations, and overdose. I also worked closely with a forensics team that we built from scratch.

There is this vast amount of data available to you when you’re right there at the point of patient care. For example, sometimes patients would come in because of out-of-control blood pressure, and we didn’t immediately know the reason for that. We started collecting data on this and realized that they had back pain and were taking nonsteroidals, which we now know interact with the disease and hypertension medications.

Observing this data and identifying these trends in this position led me to pharmacovigilance.

Pharmacovigilance is not just about observing, although it used to be. Today, it’s about being proactive and recognizing patterns that might indicate something is unusual and worth investigating further.

The faster we can get information out there, in a digestible format, to the people who are caring for patients, the better patient care that we will be able to provide.

I mean, look at the miraculous way pharma has been able to roll out the COVID-19 vaccines. In record time, we have three safe and effective vaccines. Twenty years ago, this wouldn’t have been possible.

It’s hard to remember this when you’re in pharmacovigilance. You’re usually not there to see a patient walking out of the ER or out of the hospital. I always try to remember that, in PV, we’re touching lives in ways we don’t always see.

MM: You mentioned that you worked with forensics. Can you talk a little about that?

KO: Since we were an inner-city emergency department, we saw a lot of severe reactions from drug abuse, mostly to cocaine. I even accompanied the Shelby County DEA on drug raids and acquired samples, so my colleagues and I could study the difference in the cocaine from different locations. What’s interesting is that we found there is no dose-response effect in cocaine. This kind of data helped the police better recognize when someone in their custody needed to be seen to minimize the risk of in-custody deaths.

MM: That must have been tough to observe. Did you get burned out from that kind of work?

KO: You see a lot of patients who do the same thing time and time again. I did get burned out. Too many late nights. It does take a toll on you. Hats off to those healthcare workers who work those long hours in acute care settings. It can be heart-wrenching.

MM: Let’s talk about what you’re doing day-to-day. What is the last project you completed?

KO: Well, there’s never just one project starting or completing. We recently just finished a safety system upgrade for a client, and we created custom reports for them, so the data could be used in a more meaningful way. We also recently helped another client with their intake data flows and processes.

MM: What was the client’s intake process like, and what did we recommend?

KO: We essentially were able to simplify and expedite the flow of data and enhance compliance. We helped the client eliminate multiple redundant steps in its intake process. These steps were confusing, took too long, and had too many people involved at every step of the way. Rather than going through a more direct line from A to B, all these detours were occurring. We took away the barriers and said we would get to the same endpoint easier, faster, and more accurately.

MM: Is there anything we’re doing right now that you want readers to know?

KO: Many people, even some of our clients, don’t realize the breadth of our PV team. I’ll share two examples:

We look at the pharmacovigilance ecosystem holistically. That starts with the intake of the adverse event or at the point where medical information is distributed, and it ends with the data analysis. We build and deploy intelligent processes and solutions that save people time and help them get to valuable and digestible data quickly to do their jobs more efficiently. At the moment, we’re helping organizations understand how they can use AI and natural language processing to support their medical information and call center operations. Things like virtual agents and conversational chatbots are very hot right now.

This brings me to my next point. A lot of what we do at Perficient is education. If I’m at a pharma, device, CRO, or animal health company and work a challenging 50-60 hours a week just to keep up with data, when do I have time to think about improving how my company or I work?

Unfortunately, most life sciences companies don’t have time to focus on improvements. But it’s important to sit down and talk through a problem and expand conversations into areas that feed into the pharmacovigilance ecosystem. There is a great need to better understand the landscape, the rules, and the pain points so that we can fix things practically and logically. The fact that there are so many talented people at Perficient has really helped make such conversations conducive. Fortunately, we have people here who can look at things from various perspectives. I believe it helps set us apart from our competitors.

MM: What interests you most about the industry?

KO: I get excited about working through the complexity of the drug safety regulatory network, keeping abreast of the challenges of data, and offering common-sense solutions. I’m a nerdy scientist at heart; I love keeping up with new therapeutic areas and how PV impacts the quality of patients’ lives, and how much we depend on technology. At the end of the day, we contribute to patient safety by providing the means to ensure that drugs are safe and effective.

MM: What impact will technology have in the PV space?

KO: One example is how technology helps us to understand and analyze AE data. We will need to work smarter, not harder. While there are many technology solutions available, the key to success is pairing the right solution as a fit-for-purpose agile solution. One of the biggest wake-up calls has been the value of PV data during the COVID-19 pandemic. Many of the early treatments tried in COVID-19 patients were based on historical knowledge, gained in part from legacy pharmacovigilance data.

Vicky Green, Prabha Ranganathan, and Kari at a business dinner

***

Rapid-Fire Questions

MM: What are your favorite brands or companies?

KO: I am very picky about where something is made. There are things that I will not buy if it is made in a certain geographic area.

My favorite brand of everyday cabernet is from BV Rutherford out of Napa, and for special occasions, Rothschild from the Bordeaux region of France.

My favorite brand of aircraft is Beechcraft; they make some of the most awesome innovative aircraft.

My favorite truck brands are Ford and Toyota.

My favorite perfume brand is Bond No. 9 New York.

Kari with a VTail Beech Bananza Airplane

MM: What about your favorite genre of music?

KO: I love country music, and I absolutely love Opera – Puccini is my absolute favorite composer for Opera and Mozart for classical music. And I feel happy listening to Bluegrass like Sweet Potato Pie.

MM: Coffee or tea?

KO: Definitely tea. Iced. Unsweet. Unsweet iced tea.

MM: What is the closest chain business near you?

KO: It would be a grocery store in Whitefish, MT. There are no fast-food places here, though, just local places, and they’re phenomenal. You wouldn’t believe the kind of meat we have.

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Is the Clinical Development Platform Approach Right for You?

Param Singh — Tue, 13 Apr 2021 12:27:16 +0000

Life sciences organizations typically manage their IT infrastructure and applications in silos. They implement disparate applications and manage the content and process within those applications separately. They then deploy integrations between those applications to streamline processes and share content and data with different business areas. Much of this work, including the development of integration tools and accelerators, is accomplished with the support of system integrators and consulting partners. However, the cost and complexity of clinical and safety integrations can be quite prohibitive.

Software vendors have tried to address the challenges associated with operating point solutions by creating cloud-based platforms that can replace a multitude of clinical R&D applications. These clinical development platforms, which include the likes of Oracle Clinical One and Veeva Development Cloud, are designed to encompass capabilities from traditional systems, including clinical trial management, electronic data capture, safety, electronic trial master file, and regulatory information management. The main difference by implementing platforms is that companies can optimize the collection, sharing, and tracking of data and content. They remove many manual processes by reducing data entry, reconciliation, validation, training, and user support.

This platform strategy can be extremely beneficial; however, it may not be a practical approach for all organizations to pursue. In particular, organizations with established collaborations and partnerships might find it incredibly challenging to adopt a clinical development platform in its entirety and gain all of its benefits due to how the different collaborating companies share data with each other.

Before organizations evaluate clinical development platforms, they should carefully analyze their current clinical technology landscape, map out their requirements, and develop a clear strategy that will result in a clear return on investment.

Example Evolution of an Organization Adopting a Clinical Platform Strategy

Stage 1

An organization leverages several modules/components of a clinical platform instead of implementing all functions within a unified platform. In fact, the organization doesn’t realize its clinical operations and safety/pharmacovigilance groups are using related systems from the same vendor. The organization understands processes can be streamlined by moving to a single platform, even if it’s not ready to replace all of its systems at one time.

Stage 2

In a step toward adopting key components of a clinical development platform, the organization teams up with a services provider, such as Perficient, for advisory consulting services. Working together, it is determined that the organization can immediately adopt and combine CTMS, EDC, and safety/pharmacovigilance functions by leveraging one unified platform. This will eliminate the need to replicate shared data, such as Studies, Site, Account, Contact, Addresses, etc. across systems, as well as remove the need for integrations between these systems.

Stage 3

Once the organization adopts several components of its new clinical development platform, it determines that additional clinical platform components can be adopted. This continues to reduce the need for other complex system integrations.

In-house and third-party clinical systems will continue to be part of an organization’s overall IT landscape. Ensuring these work in conjunction with the platform will be a key part of the strategy.

Contact Perficient to start your journey

At Perficient, we have the experience, skillset, and expertise to help you determine whether a clinical development platform is right for you, and if it is, create a path to move forward. Our goal is to help your organization take advantage of a comprehensive, clear strategy and the technologies that accompany it. That could be a clinical development platform in its entirety or a portion of its capabilities, with the continued use of system integrations. It could also be that this is not the right time for your company to move to a platform. Our goal is to ensure that your decisions make sense for your business.

The Clinical Development Platform Dilemma

Interest in clinical development platforms is picking up steam. And for the right reasons. These platforms substitute multiple disparate point applications – such as electronic data capture, trials management, randomization, and pharmacovigilance systems – with one unified solution.

But is a clinical development platform right for you, and if so, which one?

Download our perspective to learn the:

Brief history of clinical platforms
Potential challenges
Questions to ask before and during your search
How Perficient can help

Let’s Talk About Our Relationship (and Pharmacovigilance)

Kari Blaho-Owens — Wed, 04 Nov 2020 14:37:56 +0000

Due to social distancing, many of us found ourselves with extra time during COVID-19.

Recently on a sunny day, I was prepping some of my beehives for the upcoming winter. (By the way, anyone who thinks beekeeping is easy, please come and help! It’s hot, heavy, complicated, and completely rewarding. It’s the perfect mix of art and science.)

The preparation process reminded me of hectic weeks working with my team. Like the bees, we work in multiple places doing multiple things communicate, and in the end, we have something sweet and useful. Like in all facets of life, achieving sweetness requires a commitment to your partners.

I will go out on a limb here and tell you about our safety and pharmacovigilance (PV) practice. And just why, you may ask, do I feel compelled to do so? Often, clients are surprised by our breadth of capabilities and understanding of the space. They don’t realize we do much more than specialize in one particular system or, in some cases, one specific vendor. Nothing could be further from the truth. Just like bees, we do so much more than make honey.

Our team is well versed in the challenges faced by marketing authorization holders (MAH), having dealt with complex challenges working in pharma and the CRO industries. You will not find a more hawkish group in partnering with customers to find the best fit-for-purpose solutions for them, similar to the way a hive above is the perfect fit for its occupants.

In many ways, we can help guide our customers in streamlining their PV operations and technology platforms to become more efficient and flexible for growth, all while remaining compliant and keeping to a sane budget.

The common challenges we work with every day include choosing and harmonizing a PV technical platform that is reliable and capable of supporting a sound strategy that leverages automation and AI. The goal is to gain efficiencies as the regulatory PV burden for compliance becomes heavier.

We do not believe you have to increase headcount because there is more work or if the work is more complex. Instead, it’s about working smarter. For example, the updated GxP IX from EMA requires a thoughtful approach and change in process (i.e., the bee-minded flexibility of using all skills!), and perhaps technology, not an exponential increase in headcount. We can help ensure that, through smart working processes, a harmonized approach within your organization, and the right technology, there is a demonstrable return on investment. It’s the key to success. Perficient champions proactive PV rather than reactive PV. If proactive PV is something that your organization does not have on its radar, or this sounds a bit foreign, please, let’s talk!

If your current partner is not a good fit and is not meeting your needs, we can help. There is no challenge too great for us to step in as a strategic partner and roadmap the path to a harmonized, well-functioning PV system that is based on compliance, efficiency, usable data, and serves as the core tenants of pharmacovigilance. We include all regulatory areas, pharmaceuticals, biologics, vaccines, medical devices, animal health, cosmetovigilance. After all, we all need to be good stewards of patient safety through openness and innovation and by working together as a team.

Perficient currently has several complimentary four-hour consulting sessions that show our bona fides in solving complex PV issues. While four hours won’t solve everything, it is an excellent opportunity for us to demonstrate how we would approach a current issue or a strategic roadmap. Case intake overwhelmed? Data not harmonized and challenging to interpret? No clear path defined for alleviating pain points? Geographical PV groups leading to bespoke processes or technology? These challenges and more are what drives us to partner with our clients in a different and more meaningful way.

Our guiding principle with our clients opens up opportunities to have meaningful conversations that can prevent and solve some of the above issues.

I want to share a mini case study that will hopefully give you a better idea of how we can help companies just like yours.

Problem

The company had geographically separate PV groups. Both teams covered the same products. Cases were processed by the team closest, by distance, to the area where the case was reported. Both teams had the same case processing workflow. Local labeling was identical. The two PV groups worked under one global medical monitoring team, which was based in one of the geographic areas. The two PV groups disagreed on nearly every case regarding seriousness, causality, and reportability.

PV Group 1 took the approach of evaluating the context of the events reported, concomitant medications, co-morbid conditions, etc.

PV Group 2 wanted the approach of using the EMA IME list as an absolute for seriousness criteria. This guidance document was released in its latest form in September 2020.

The request from our client was to configure the database to allow for separate seriousness and causality assessments for the same case by the two different PV groups. This internal compromise between the two groups would have resulted in splitting the medical assessment team and de-harmonizing its data. It would be a difficult and expensive change to its AE database but was as close as the groups could agree.

The client had two options:

Perform the configuration change per the client’s requirements, which would have involved a new SOW and be time- and resource-expensive.
Engage our business development executive with the team, meet with the client, and have an open partnership discussion.

Solution

The client chose #2. We came to the meeting with open ears, listened, and laid out the risks and the benefits of the request. We discussed the request’s impact, including regulatory risk, data integrity, differences in serious case counts for the same set of data, anticipated work to revise internal SOPs, etc.

After a small amount of what we call “partnership stewardship,” we were able to give the client a different view of the impact of its request. It prompted both PV groups to come back to the table to find a neutral ground to avoid the risks, which were not insignificant. We ended up with a more robust collaborative medical assessment and medical monitoring of its product while following regional guidances.

Cost

It was free. We invested our time into the partnership to help a client through a complex PV conundrum.

If your PV partner doesn’t engage in meaningful conversations with your PV team, it might be time to see if you can “connect” with a new partner that genuinely cares about your success.

I am here to discuss your challenges. Please don’t hesitate to reach out to me personally, and tell me you came across this blog post. I’m always interested in hearing how people find us.

Pharmacovigilance During COVID-19: Finding the Best Information

Kari Blaho-Owens — Wed, 25 Mar 2020 13:18:43 +0000

There is no question that the pandemic COVID-19 has transformed life as we know it today. We are now operating in a different pharmacovigilance (PV) paradigm, adapting as we move daily. While patient safety remains the first priority, AEs will continue to come in for processing, and daily PV activities will continue. New therapeutic information for the treatment of COVID-19 and potential COVID-19drug interactions to consider are part of the influx of clinical and PV data.

How can we use the PV data, and how are scientists, clinicians, and FDA pivoting so quickly to push drugs into clinical trials for the treatment of COVID-19? Where can you find the best sources for trials and clinical data regarding evolving COVID-19 story? How can we help in our daily PV roles?

President Trump, on Friday, March 13, 2020, declared a national state of emergency. With that move, and with previous forward-thinking actions such as “right to try,” he untangled the regulatory burden so that healthcare providers, patients, regulatory agencies, and scientists could have all tools available to help patients. President Trump has also strategically met with manufacturers of critical medical supplies to ramp up production and, in partnership with the FDA, ensure that supply chains remain steady. FDA with an unprecedented Twitter feed asking for supply chain information:

.@US_FDA suggests companies make public their inventory, production schedule and a hotline number to address questions regarding availability of reagents and other supplies needed for #COVID19 testing. If you have an allocation plan to maximize efficient testing, please post. pic.twitter.com/LdX3P7ZT1m

— Anand Shah, M.D. (@AnandShahFDA) March 17, 2020

When it comes to speeding up the identification of potential treatment options for COVID-19 and finding a way to slow or decrease the morbidity and mortality, pharmacovigilance data plays an important role. It’s critical to understand what a drug can and cannot do.

For COVID-19, the most successful early information on effective treatment is with known drugs. As of March 21, 2020, the combination of hydroxychloroquine (known for anti-malarial and used since the 1940s) with azithromycin looks very promising. “Look” and “anectdotal” are not scientific evidence, but is it enough in a global pandemic?

In a global pandemic, we need visibility and reliable sources of disease progression and the impact of any early trials.

Where can you find accurate data, and how can those performing pharmacovigilance activities help? We know most have made the transition to working remotely, so in order to best collaborate, the information must be readily available.

Here is what we have found to be of value for PV for COVID-19 data:

PubMed (Dedicated website for COVID-19 clinical data that is available for tracking publications and information in real time)
1. https://www.ncbi.nlm.nih.gov/research/coronavirus/
Johns Hopkins University (Tracks coronavirus COVID-19 global cases)
1. https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
National Institutes of Health (NIH)
1. https://www.nih.gov/coronavirus
Centers for Disease Control (CDC)
1. https://www.coronavirus.gov
World Health Organization
1. https://www.who.int/emergencies/diseases/novel-coronavirus-2019
Medscape (For healthcare providers; great up to date information and links)
1. medscape.com
Your own PV data
1. If there are drugs with similar mechanisms of action, take a look. We have often spoken of the value of data. Hydroxychloroquine and azithromycin are not new drugs; your own pharmacovigilance data may hold valuable information as well.

Here are some examples of ongoing clinical trials that are repurposing existing therapies. More can be found at www.fda.gov or www.clinicaltrials.gov.

Repurposing existing therapies:

Remdesivir: FDA approves Phase III trials with remdesivir, an anti-viral as a potential treatment for COVID-19 patients under emergency use, and expanded access to the drug under the new IND requirements and patient access. As of March 19, 2020, 250 patients have received the drug.

Chloroquine/Hydroxychloroquine: March 19, 2020: FDA approves chloroquine for use in COVID-19 patients. A long staple of prevention and treatment of malaria (a parasitic infection), as well as having immunosuppressant activities that may help decrease viral replication, is now available. The combination of hydroxychloroquine and azithromycin was quickly added.

Sarilumab – An IL-6 receptor antibody to decrease the pulmonary inflammation seen in COVID-19 patients hospitalized with severe COVID-19 infection. On March 16, 2020, a trial began to determine if the attenuation of pulmonary inflammation in COVID-19 patients was clinically beneficial.

Our pharmacovigilance and safety team is dedicated to real-time surveillance and technology support. We also understand the pharmacology behind your products. During this challenging time, if you need additional support, please reach out. We are ready to spool up quickly and help if additional PV resources are required. Please contact Kari Blaho-Owens, Ph.D., Director PV and Safety, at kari.owens@perficient.com for more information.

22 Reasons To Attend Thursday’s Pharmacovigilance Surveillance Webinar

Kari Blaho-Owens — Tue, 04 Feb 2020 15:00:32 +0000

The challenge with all pharmacovigilance and safety surveillance is that it’s quite complicated. There is a lot of data and very few technical solutions that make analyzing safety data relatively simple. That’s where Perficient comes in.

Join me, Kari Blaho-Owens, Ph.D., Director of Pharmacovigilance and Safety, Perficient, on February 6, 2020, at 10 AM CT, for a webinar titled “Raise the Bar With Real-Time Pharmacovigilance Surveillance” in which I’ll give a demonstration of PV Hawk, a risk management tool that gives you quick access to aggregate data for the meaningful analysis of AE and PQC data — all in real-time and across all of your safety surveillance practices and interested parties.

This webinar (and PV Hawk) is for you if you catch yourself saying any of these 22 things:

“I am frustrated with the surveillance practices we have or the lack of them. It’s too cumbersome and too much work.”
“What we do or don’t do is risky – but I can’t say that out loud.”
“I hate the flat reports we get that make it impossible to interpret the data.”
“I have to go to multiple sources to get the right data, and then I have to merge it.”
“If I have to look at another Excel sheet of data from the database and try to make a pivot table with it, I will lose my mind.”
“I have to run cumbersome reports in the database, and I hate it; it takes too much time and the reports don’t work half of the time.”
“No one understands what the data really means – isn’t there enough to do without having to sit and look at numbers?”
“I have no in-house expert to tell me how to do this – it’s not iterative or intuitive.”
“There are too many people trying to do data surveillance on the PV data…too many cooks in the kitchen.”
“We have a solution, but it’s terrible.”
“Our solution creates too much noise.”
“I need something I can share across multiple groups that everyone’s going to understand.”
“What good does it do to look at stale data? I can’t change what happened last month.”
“My data needs change, and I can’t get the right data half of the time; no one listens to me.”
“I need an easy solution with graphics where I can explain the AE data. I can explain it to multiple groups, from my intake group to executive management, who want to know the risk profile of a profile before marketing goes on some campaign to advertise my products without telling pharmacovigilance.”
“We aren’t supposed to do trending in Excel…where data might be corrupt.”
“I need to share stuff, and I can’t share pivot tables that I’m not really confident in because I can’t admit I don’t know how to really use Excel.”
“I wish I had something that did what I actually need.”
“The other solutions we’ve tried to take a Nobel Prize in IT to navigate through, and it takes forever to get an answer.”
“Everyone is running different reports, and none of the data in them matches.”
“I know data surveillance is essential, but I have tons of other stuff I have to do.”
“Why is surveillance of PV data so hard? It shouldn’t be this hard.”

So, to learn how to raise the bar with real-time pharmacovigilance surveillance, register for the upcoming webinar. If you have any questions in the meantime, feel free to reach out to me at kari.owens@perficient.com.

Join Us At Oracle Industry Connect 2018

Eugene Sefanov — Thu, 29 Mar 2018 12:21:25 +0000

Perficient is sponsoring Oracle Industry Connect April 10-11 in New York City, and we would like our valued clients to be there. Several key representatives from our life sciences practice will be available to discuss any of your ongoing or upcoming initiatives.

Mike Grossman, General Manager
Dennis Dougherty, Business Development Executive
Rudolf Coetzee, Business Development Executive
Vicky Green, Business Development Executive

If you are interested in attending, please let us know via the contact form at the end of this page. Admission is free, but it’s an invitation-only event. We will have Oracle send you a private invitation.

If you would like to schedule a meeting with the team, let us know and we will arrange one for you.

For those of you who are able to attend, we would also like to invite you to the following roundtable that we are hosting during lunch on Tuesday, April 10:

—

Moving to the Cloud with a Strategic Partner

Faster implementation timelines and reduced costs are just two reasons why the cloud has become the standard in life sciences.

In this roundtable discussion, learn how you can implement solutions such as Oracle’s Siebel Clinical Trial Management System, Oracle Argus Safety, Oracle Health Sciences Data Management Workbench, Oracle Life Sciences Data Hub, Oracle Clinical, Oracle Clinical Remote Data Capture, and Oracle Thesaurus Management System in the cloud by leveraging a partner.

Along with end-to-end managed services, an experienced partner can provide you with a set of complementary services, such as data migration, integrations, and validation.

Bring your company’s situation to the table, and we’ll discuss the best approach to move forward.

The Connect Zone, Americas Hall I, Third Floor | Table 14
Tuesday, April 10
12:00 p.m. – 1:30 p.m.
Lunch will be served at the table

We look forward to seeing you at the event!

Interest In AI And Cognitive Is Rising In Pharma

Eugene Sefanov — Tue, 13 Feb 2018 12:30:56 +0000

Artificial intelligence (AI), cognitive computing, and machine learning are becoming more common in the industry. The need to scour and analyze large sets of data is giving life sciences companies new intelligence that would never have been realized before. The technology is making a big impact on healthcare decisions and patients.

When it comes to addiction and substance abuse, patient risk models are helping predict and prevent incidents of relapse. Artificial intelligence is helping doctors identify treatment options while providing supporting evidence. While AI is driving precision medicine, it’s also being used by pharmaceutical companies to gain insight into consumer behavior and expectations.

Jason Andree, senior brand manager of the Cough & Cold Portfolio at GlaxoSmithKline North America, shared how GSK is using cognitive technology to promote its Theraflu brand. The company is using IBM Watson to enable consumers to interact with advertisements within a mobile app, by asking questions (through voice or text) related to the flu or the Theraflu product.

To learn about other trends that we can also expect to see in 2018, click here.

Building Better Safety Profiles With Real-World Data & Evidence

Eugene Sefanov — Tue, 30 Jan 2018 12:30:20 +0000

The use of real-world data has exploded in recent years and will continue playing a crucial role in 2018. Almost every major pharmaceutical and medical device company conducts real-world studies to build better safety profiles for their products, as well as support initial study findings.

Real-world data can come from a variety of sources including insurance claims databases, medical records, national registries, social media, and mobile devices.

According to Professor William Sandborn, M.D., chief of the Division of Gastroenterology at the University of California San Diego, “Real-world evidence plays an important role in helping healthcare providers evaluate a therapy’s effectiveness and safety in routine medical practice against clinical trial results.”

Over the past year, many companies have reported results that confirm the effectiveness of their products and highlight how one product is better than another. Companies have also shown that they can achieve better outcomes.

The importance of real-world data is evident across the industry and can be heard in presentations delivered by scientific leaders. When commenting on a particular study, Rory O’Connor, M.D., chief medical officer of Pfizer Internal Medicine, said: “We believe real-world data analyses via the ACROPOLIS program are helping to advance deeper levels of insight into how different patient demographics, comorbidities, and disease severity factor into how Eliquis may impact patient outcomes.”

Fortunately, the FDA has also increased its focus on the benefits of real-world data and evidence to understand a product’s safety and effectiveness.

In an August 2017 guidance document, the regulator said, “While FDA encourages the use of relevant and reliable RWD, this guidance neither mandates its use nor restricts other means of providing evidence to support regulatory decision-making.”

To learn about other trends that we can also expect to see in 2018, click here.

EMA Issues Brexit Guidance To Pharma

Indy Ahluwalia — Wed, 29 Nov 2017 13:51:07 +0000

Pharmaceutical companies selling their products in the UK need to consider the impact Brexit will have on their operations. Some changes will need to be made before the UK leaves the European Union on March 30, 2019.

In a press release, the European Medicines Agency (EMA) said:

“The guidance document outlines the practical and simplified requirements that companies should follow when they apply for changes to their marketing authorisation to allow for the continued marketing of their medicine in the European Economic Area after the UK withdraws from the EU. The guidance has been prepared on the basis that the UK will become a third country as of 30 March 2019. It should be read in conjunction with the Questions and answers related to the United Kingdom’s withdrawal from the European Union with regard to the medicinal products for human and veterinary use within the framework of the centralised procedure published in May 2017.”

The following questions are answered in the document:

1. Can I group Brexit-related variations?

2. How to classify Brexit-related changes impacting on the manufacturing activities for my medicinal product?

3. Can I submit several changes relating to manufacturing of the active substance or finished product under a single Type II variation?

4. How can I submit an application for the transfer of a marketing authorisation for my products and what would the applicable fees be?

4a. How to handle planned or ongoing regulatory procedures during the transfer of marketing authorisation?

4b. Is it possible to submit a transfer of the orphan designation in parallel with a transfer of the marketing authorisation?

4c. Is there any possibility to simplify transfer applications when these are Brexit related?

4d. Can requirement for mock-ups be waived for Transfers?

5. How can I submit a transfer or change in the name/address of an orphan drug designation sponsor for my products? (for medicines for human use)

6. How do I submit changes to Qualified Person for Pharmacovigilance (QPPV) and/or changes in the Pharmacovigilance Master File (PSMF)location? (for medicines for human use)

7. How do I submit changes to QPPV? (for veterinary medicines)

8. How do I submit changes to the person responsible of scientific services and to the person responsible for batch recall and quality defects? (for medicines for human use)

9. How do I submit changes to the person responsible for batch recall and quality defects? (for veterinary medicines)

To read the guidance, click here.

If you are interested in learning how Perficient can help you prepare for Brexit or help you evaluate the impact of new and proposed regulatory rules on your organisation, please reach out.

Top 5 Pharma & Medical Device Blog Posts From October 2017

Eugene Sefanov — Wed, 01 Nov 2017 11:30:04 +0000

Now that November is here, I thought it would be neat to look back at what our readers found most interesting last month. Below are the top five blog posts Perficient’s life sciences practice wrote in October – they’re ranked in order of popularity, with number one being the most viewed piece.

As always, thank you for your continued support – our team finds it very rewarding to have you as a reader.